A Survey of Energy-Efficient Techniques for 5G Networks and Challenges Ahead
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paper_title: The global footprint of mobile communications: The ecological and economic perspective

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This article quantifies the global carbon footprint of mobile communication systems, and discusses its ecological and economic implications. Using up-to-date data and life cycle assessment models, we predict an increase of CO2 equivalent emissions by a factor of three until 2020 compared to 2007, rising from about 86 to 235 Mto CO2e, suggesting a steeper increase than predicted in the well-known SMART2020 report. We provide a breakdown of the global carbon footprint, which reveals that production of mobile devices and global radio access network operation will remain the major contributors, accompanied by an increasing share of emissions due to data transfer in the backbone resulting from rising mobile traffic volumes. The energy bill due to network operation will gain increasing importance in cellular business models. Furthermore, technologies to reduce energy consumption are considered a key enabler for the spread of mobile communications in developing countries. Taking into account several scenarios of technological advancement and rollout, we analyze the overall energy consumption of global radio access networks and illustrate the saving potential of green communication technologies. We conclude that, conditioned on quick implementation and alongside other "classical" improvements of spectral efficiency, these technologies offer the potential to serve three orders of magnitude more traffic with the same overall energy consumption as today.
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paper_title: Power Control for Wireless Data

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With cellular phones mass-market consumer items, the next frontier is mobile multimedia communications. This situation raises the question of how to perform power control for information sources other than voice. To explore this issue, we use the concepts and mathematics of microeconomics and game theory. In this context, the quality of service of a telephone call is referred to as the "utility" and the distributed power control problem for a CDMA telephone is a "noncooperative game." The power control algorithm corresponds to a strategy that has a locally optimum operating point referred to as a "Nash equilibrium." The telephone power control algorithm is also "Pareto efficient," in the terminology of game theory. When we apply the same approach to power control in wireless data transmissions, we find that the corresponding strategy, while locally optimum, is not Pareto efficient. Relative to the telephone algorithm, there are other algorithms that produce higher utility for at least one terminal, without decreasing the utility for any other terminal. This article presents one such algorithm. The algorithm includes a price function proportional to transmitter power. When terminals adjust their power levels to maximize the net utility (utility-price), they arrive at lower power levels and higher utility than they achieve when they individually strive to maximize utility.
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paper_title: An energy-efficient approach to power control and receiver design in wireless data networks

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In this paper, the cross-layer design problem of joint multiuser detection and power control is studied, using a game-theoretic approach that focuses on energy efficiency. The uplink of a direct-sequence code-division multiple-access data network is considered, and a noncooperative game is proposed in which users in the network are allowed to choose their uplink receivers as well as their transmit powers to maximize their own utilities. The utility function measures the number of reliable bits transmitted by the user per joule of energy consumed. Focusing on linear receivers, the Nash equilibrium for the proposed game is derived. It is shown that the equilibrium is one where the powers are signal-to-interference-plus-noise ratio-balanced with the minimum mean-square error (MMSE) detector as the receiver. In addition, this framework is used to study power-control games for the matched filter, the decorrelator, and the MMSE detector; and the receivers' performance is compared in terms of the utilities achieved at equilibrium (in bits/joule). The optimal cooperative solution is also discussed and compared with the noncooperative approach. Extensions of the results to the case of multiple receive antennas are also presented. In addition, an admission-control scheme based on maximizing the total utility in the network is proposed.
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paper_title: Cloud technologies for flexible 5G radio access networks

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The evolution toward 5G mobile networks will be characterized by an increasing number of wireless devices, increasing device and service complexity, and the requirement to access mobile services ubiquitously. Two key enablers will allow the realization of the vision of 5G: very dense deployments and centralized processing. This article discusses the challenges and requirements in the design of 5G mobile networks based on these two key enablers. It discusses how cloud technologies and flexible functionality assignment in radio access networks enable network densification and centralized operation of the radio access network over heterogeneous backhaul networks. The article describes the fundamental concepts, shows how to evolve the 3GPP LTE a
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paper_title: Energy Efficiency in Wireless Networks via Fractional Programming Theory

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This monograph presents a unified framework for energy efficiency maximization in wireless networks via fractional programming theory. The definition of energy efficiency is introduced, with reference to single-user and multi-user wireless networks, and it is observed how the problem of resource allocation for energy efficiency optimization is naturally cast as a fractional program. An extensive review of the state-of-the-art in energy efficiency optimization by fractional programming is provided, with reference to centralized and distributed resource allocation schemes. A solid background on fractional programming theory is provided. The key-notion of generalized concavity is presented and its strong connection with fractional functions described. A taxonomy of fractional problems is introduced, and for each class of fractional problem, general solution algorithms are described, discussing their complexity and convergence properties. The described theoretical and algorithmic framework is applied to solve energy efficiency maximization problems in practical wireless networks. A general system and signal model is developed which encompasses many relevant special cases, such as one-hop and two-hop heterogeneous networks, multi-cell networks, small-cell networks, device-to-device systems, cognitive radio systems, and hardware-impaired networks, wherein multiple-antennas and multiple subcarriers are possibly employed. Energy-efficient resource allocation algorithms are developed, considering both centralized, cooperative schemes, as well as distributed approaches for self-organizing networks. Finally, some remarks on future lines of research are given, stating some open problems that remain to be studied. It is shown how the described framework is general enough to be extended in these directions, proving useful in tackling future challenges that may arise in the design of energy-efficient future wireless networks.
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paper_title: Dynamic Base Station Switching-On/Off Strategies for Green Cellular Networks

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In this paper, we investigate dynamic base station (BS) switching to reduce energy consumption in wireless cellular networks. Specifically, we formulate a general energy minimization problem pertaining to BS switching that is known to be a difficult combinatorial problem and requires high computational complexity as well as large signaling overhead. We propose a practically implementable switching-on/off based energy saving (SWES) algorithm that can be operated in a distributed manner with low computational complexity. A key design principle of the proposed algorithm is to turn off a BS one by one that will minimally affect the network by using a newly introduced notion of network-impact, which takes into account the additional load increments brought to its neighboring BSs. In order to further reduce the signaling and implementation overhead over the air and backhaul, we propose three other heuristic versions of SWES that use the approximate values of network-impact as their decision metrics. We describe how the proposed algorithms can be implemented in practice at the protocol-level and also estimate the amount of energy savings through a first-order analysis in a simple setting. Extensive simulations demonstrate that the SWES algorithms can significantly reduce the total energy consumption, e.g., we estimate up to 50-80% potential savings based on a real traffic profile from a metropolitan urban area.
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paper_title: What Will 5G Be?

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What will 5G be? What it will not be is an incremental advance on 4G. The previous four generations of cellular technology have each been a major paradigm shift that has broken backward compatibility. Indeed, 5G will need to be a paradigm shift that includes very high carrier frequencies with massive bandwidths, extreme base station and device densities, and unprecedented numbers of antennas. However, unlike the previous four generations, it will also be highly integrative: tying any new 5G air interface and spectrum together with LTE and WiFi to provide universal high-rate coverage and a seamless user experience. To support this, the core network will also have to reach unprecedented levels of flexibility and intelligence, spectrum regulation will need to be rethought and improved, and energy and cost efficiencies will become even more critical considerations. This paper discusses all of these topics, identifying key challenges for future research and preliminary 5G standardization activities, while providing a comprehensive overview of the current literature, and in particular of the papers appearing in this special issue.
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paper_title: Energy-Efficient Resource Allocation for MIMO-OFDM Systems Serving Random Sources With Statistical QoS Requirement

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This paper optimizes resource allocation that maximizes the energy efficiency (EE) of wireless systems with statistical quality of service (QoS) requirement, where a delay bound and its violation probability need to be guaranteed. To avoid wasting energy when serving random sources over wireless channels, we convert the QoS exponent, a key parameter to characterize statistical QoS guarantee under the framework of effective bandwidth and effective capacity, into multi-state QoS exponents dependent on the queue length. To illustrate how to optimize resource allocation, we consider multi-input-multi-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. A general method to optimize the queue length based bandwidth and power allocation (QRA) policy is proposed, which maximizes the EE under the statistical QoS constraint. A closed-form optimal QRA policy is derived for massive MIMO-OFDM system with infinite antennas serving the first order autoregressive source. The EE limit obtained from infinite delay bound and the achieved EEs of different policies under finite delay bounds are analyzed. Simulation and numerical results show that the EE achieved by the QRA policy approaches the EE limit when the delay bound is large, and is much higher than those achieved by existing policies considering statistical QoS provision when the delay bound is stringent.
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paper_title: Optimal Energy-Efficient Power Allocation for OFDM-Based Cognitive Radio Networks

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This letter investigates the energy-efficient power allocation for orthogonal frequency division multiplexing (OFDM) based cognitive radio networks (CRNs). The problem is to maximize the energy-efficiency measured using the "throughput per Joule" metric subject to the total transmit power and interference constraints. It is then transformed into an equivalent convex problem using parametric programming. Furthermore, an optimal iterative algorithm based on convex optimization theory and parametric programming is proposed. The numerical results show that the proposed optimal algorithm can achieve higher energy-efficiency than that obtained by solving the original problem directly because of its non-convexity. Energy-efficiency maximization can also achieve a good tradeoff between capacity and energy in CRNs.
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paper_title: Energy Efficiency Analysis of Cooperative Jamming in Cognitive Radio Networks With Secrecy Constraints

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We investigate energy-efficient cooperation for secrecy in cognitive radio networks. In particular, we consider a four-node cognitive scenario where the secondary receiver is treated as a potential eavesdropper with respect to the primary transmission. The cognitive transmitter should ensure that the primary message is not leaked to the secondary user by using cooperative jamming. We investigate the optimal power allocation and power splitting at the secondary transmitter for our cognitive model to maximize the secondary energy efficiency (EE) under secrecy constraints. We formulate and analyze an important EE Stackelberg game between the two transmitters aiming at maximizing their utilities. We illustrate the analytical results through our geometrical model, highlighting the EE performance of the system and the impact of the Stackelberg game.
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paper_title: A Repeated Game Formulation of Energy-Efficient Decentralized Power Control

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Decentralized multiple access channels where each transmitter wants to selfishly maximize his transmission energy-efficiency are considered. Transmitters are assumed to choose freely their power control policy and interact (through multiuser interference) several times. It is shown that the corresponding conflict of interest can have a predictable outcome, namely a finitely or discounted repeated game equilibrium. Remarkably, it is shown that this equilibrium is Pareto-efficient under reasonable sufficient conditions and the corresponding decentralized power control policies can be implemented under realistic information assumptions: only individual channel state information and a public signal are required to implement the equilibrium strategies. Explicit equilibrium conditions are derived in terms of minimum number of game stages or maximum discount factor. Both analytical and simulation results are provided to compare the performance of the proposed power control policies with those already existing and exploiting the same information assumptions namely, those derived for the one-shot and Stackelberg games.
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paper_title: Achieving maximum energy-efficiency in multi-relay OFDMA cellular networks: a fractional programming approach

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In this paper, the joint power and subcarrier allocation problem is solved in the context of maximizing the energy-efficiency (EE) of a multi-user, multi-relay orthogonal frequency division multiple access (OFDMA) cellular network, where the objective function is formulated as the ratio of the spectral-efficiency (SE) over the total power dissipation. It is proven that the fractional programming problem considered is quasi-concave so that Dinkelbach's method may be employed for finding the optimal solution at a low complexity. This method solves the above-mentioned master problem by solving a series of parameterized concave secondary problems. These secondary problems are solved using a dual decomposition approach, where each secondary problem is further decomposed into a number of similar subproblems. The impact of various system parameters on the attainable EE and SE of the system employing both EE maximization (EEM) and SE maximization (SEM) algorithms is characterized. In particular, it is observed that increasing the number of relays for a range of cell sizes, although marginally increases the attainable SE, reduces the EE significantly. It is noted that the highest SE and EE are achieved, when the relays are placed closer to the BS to take advantage of the resultant line-of-sight link. Furthermore, increasing both the number of available subcarriers and the number of active user equipment (UE) increases both the EE and the total SE of the system as a benefit of the increased frequency and multi-user diversity, respectively. Finally, it is demonstrated that as expected, increasing the available power tends to improve the SE, when using the SEM algorithm. By contrast, given a sufficiently high available power, the EEM algorithm attains the maximum achievable EE and a suboptimal SE.
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paper_title: Energy-Efficient Precoding for Multiple-Antenna Terminals

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The problem of energy-efficient precoding is investigated when the terminals in the system are equipped with multiple antennas. Considering static and fast-fading multiple-input multiple-output (MIMO) channels, the energy-efficiency is defined as the transmission rate to power ratio and shown to be maximized at low transmit power. The most interesting case is the one of slow fading MIMO channels. For this type of channels, the optimal precoding scheme is generally not trivial. Furthermore, using all the available transmit power is not always optimal in the sense of energy-efficiency [which, in this case, corresponds to the communication-theoretic definition of the goodput-to-power (GPR) ratio]. Finding the optimal precoding matrices is shown to be a new open problem and is solved in several special cases: 1. when there is only one receive antenna; 2. in the low or high signal-to-noise ratio regime; 3. when uniform power allocation and the regime of large numbers of antennas are assumed. A complete numerical analysis is provided to illustrate the derived results and stated conjectures. In particular, the impact of the number of antennas on the energy-efficiency is assessed and shown to be significant.
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paper_title: Energy Efficiency Optimization of 5G Radio Frequency Chain Systems

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With the massive multi-input multi-output (MIMO) antennas technology adopted for the fifth generation (5G) wireless communication systems, a large number of radio frequency (RF) chains have to be employed for RF circuits. However, a large number of RF chains not only increase the cost of RF circuits but also consume additional energy in 5G wireless communication systems. In this paper we investigate energy and cost efficiency optimization solutions for 5G wireless communication systems with a large number of antennas and RF chains. An energy efficiency optimization problem is formulated for 5G wireless communication systems using massive MIMO antennas and millimeter wave technology. Considering the nonconcave feature of the objective function, a suboptimal iterative algorithm, i.e., the energy efficient hybrid precoding (EEHP) algorithm is developed for maximizing the energy efficiency of 5G wireless communication systems. To reduce the cost of RF circuits, the energy efficient hybrid precoding with the minimum number of RF chains (EEHP-MRFC) algorithm is also proposed. Moreover, the critical number of antennas searching (CNAS) and user equipment number optimization (UENO) algorithms are further developed to optimize the energy efficiency of 5G wireless communication systems by the number of transmit antennas and UEs. Compared with the maximum energy efficiency of conventional zero-forcing (ZF) precoding algorithm, numerical results indicate that the maximum energy efficiency of the proposed EEHP and EEHP-MRFC algorithms are improved by 220% and 171%, respectively.
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paper_title: Pricing and Power Control in a Multicell Wireless Data Network

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We consider distributed power control in a multicell wireless data system and study the effect of pricing transmit power. Drawing on the earlier work of Goodman and Mandayam (see IEEE Personal Commun. Mag., vol.7, p.48-54, 2000), we formulate the QoS of a data user via a utility function measured in bits per Joule. We consider distributed power control, modeled as a noncooperative game, where users maximize their utilities in a multicell system. Base station assignment based on received signal strength as well as received signal-to-interference ratio (SIR) are considered jointly with power control. Our results indicate that for both assignment schemes, such a procedure results in an inefficient operating point (Nash equilibrium) for the entire system. We introduce pricing of transmit power as a mechanism for influencing data user behavior and our results show that the distributed power control based on maximizing the net utility (utility minus the price) results in improving the Pareto efficiency of the resulting operating point. Variations of pricing based on global and local loading in cells are considered as a means of improving the efficiency of wireless data networks. Finally, we discuss the improvement in utilities through a centralized scheme where each base station (BS) calculates the best SIR to be targeted by the terminals it is assigned.
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paper_title: Power-Delay Tradeoff With Predictive Scheduling in Integrated Cellular and Wi-Fi Networks

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The explosive growth of global mobile traffic has led to rapid growth in the energy consumption in communication networks. In this paper, we focus on the energy-aware design of the network selection, subchannel, and power allocation in cellular and Wi-Fi networks, while taking into account the traffic delay of mobile users. Based on the two-timescale Lyapunov optimization technique, we first design an online Energy-Aware Network Selection and Resource Allocation (ENSRA) algorithm, which yields a power consumption within $O\left({\frac{1}{V}} \right)$ bound of the optimal value, and guarantees an $O\left(V \right)$ traffic delay for any positive control parameter $V$ . Motivated by the recent advancement in the accurate estimation and prediction of user mobility, channel conditions, and traffic demands, we further develop a novel predictive Lyapunov optimization technique to utilize the predictive information, and propose a Predictive Energy-Aware Network Selection and Resource Allocation (P-ENSRA) algorithm. We characterize the performance bounds of P-ENSRA in terms of the power-delay tradeoff theoretically. To reduce the computational complexity, we finally propose a Greedy Predictive Energy-Aware Network Selection and Resource Allocation (GP-ENSRA) algorithm, where the operator solves the problem in P-ENSRA approximately and iteratively. Numerical results show that GP-ENSRA significantly improves the power-delay performance over ENSRA in the large delay regime. For a wide range of system parameters, GP-ENSRA reduces the traffic delay over ENSRA by 20–30% under the same power consumption.
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paper_title: On the Energy Efficiency-Spectral Efficiency Trade-Off of Distributed MIMO Systems

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In this paper, the trade-off between energy efficiency (EE) and spectral efficiency (SE) is analyzed for both the uplink and downlink of the distributed multiple-input multiple-output (DMIMO) system over the Rayleigh fading channel while considering different types of power consumption models (PCMs). A novel tight closed-form approximation of the DMIMO EE-SE trade-off is presented and a detailed analysis is provided for the scenario with practical antenna configurations. Furthermore, generic and accurate low and high-SE approximations of this trade-off are derived for any number of radio access units (RAUs) in both the uplink and downlink channels. Our expressions have been utilized for assessing both the EE gain of DMIMO over co-located MIMO (CMIMO) and the incremental EE gain of DMIMO in the downlink channel. Our results reveal that DMIMO is more energy efficient than CMIMO for cell edge users in both the idealistic and realistic PCMs; whereas in terms of the incremental EE gain, connecting the user terminal to only one RAU is the most energy efficient approach when a realistic PCM is considered.
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paper_title: Outage Probability and Energy Efficiency of Cooperative MIMO with Antenna Selection

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This paper compares the energy efficiency of some cooperative MIMO schemes in wireless networks. By energy efficiency we denote the spectral efficiency seen at the receiver normalized by the total energy consumption, which includes the circuitry, the efficiency of the power amplifier, and the transmission rate. We focus on transmit antenna selection (TAS) and switch and stay combining (SSC) at the receiver. The performance of TAS+SSC is compared to that of TAS and maximal ratio combining (MRC), and to that of transmit/receive beamforming using a singular value decomposition (SVD) technique. We derive closed-form outage probability expressions, and analyze the effect of selecting the antenna from the source to optimize the communication with the relay or with the destination. Our results show that selecting the antennas with respect to the destination is in general a better option when the energy consumption is accounted. Moreover, some power allocation strategies are described and the comparison of the schemes in terms of energy efficiency reveals a considerable improvement with the use of TAS+SSC for low to moderate spectral efficiency, while beamforming outperforms the other schemes for high spectral efficiency when the number of antennas at each node is small.
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paper_title: Energy Efficiency and Interference Neutralization in Two-Hop MIMO Interference Channels

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The issue of energy-aware resource allocation in an amplify-and-forward (AF) relay-assisted multiple-antenna interference channel (IC) is considered. A novel interference neutralization (IN) scheme is proposed for relay design and, based on the IN relay matrix design, two algorithms are developed to jointly allocate the users' transmit powers, beamforming (BF) and receive filters. The first algorithm considers a competitive scenario and employs a noncooperative game-theoretic approach to maximize the individual energy efficiency (EE) of each communication link, defined as the ratio of the achievable rate over the consumed power. The resulting algorithm converges to a unique fixed point, has limited complexity, and can be implemented in a distributed fashion. The second algorithm employs fractional programming tools and sequential convex optimization to centrally allocate the users' transmit powers, BF, and receive filters for global energy efficiency (GEE) maximization. The resulting algorithm is guaranteed to converge and has limited computational complexity. Numerical results show that the competitive IN design achieves virtually the same performance as the cooperative design if IN is feasible, while the gap is small if perfect IN is not achievable.
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paper_title: Pricing-Based Distributed Energy-Efficient Beamforming for MISO Interference Channels

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In this paper, we consider the problem of maximizing the weighted sum energy efficiency (WS-EE) for multi-input single-output (MISO) interference channels (ICs), which are well acknowledged as general models of heterogeneous networks (HetNets), multicell networks, etc. To address this problem, we develop an efficient distributed beamforming algorithm based on a pricing mechanism. Specifically, we carefully introduce a price metric for distributed beamforming design, which fortunately allows efficient closed-form solutions to the per-user beam-vector optimization problem. The convergence of the distributed pricing-based beamforming design is theoretically proven. Furthermore, we present an implementation strategy of the proposed distributed algorithm with limited information exchange. Numerical results show that our algorithm converges much faster than existing algorithms, while yielding comparable, sometimes even better performance in terms of the WS-EE. Finally, by taking the backhaul power consumption into account, it is interesting to show that the proposed algorithm with limited information exchange achieves better WS-EE than the full information exchange-based algorithm in some special cases.
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paper_title: An energy-efficient approach to power control and receiver design in wireless data networks

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In this paper, the cross-layer design problem of joint multiuser detection and power control is studied, using a game-theoretic approach that focuses on energy efficiency. The uplink of a direct-sequence code-division multiple-access data network is considered, and a noncooperative game is proposed in which users in the network are allowed to choose their uplink receivers as well as their transmit powers to maximize their own utilities. The utility function measures the number of reliable bits transmitted by the user per joule of energy consumed. Focusing on linear receivers, the Nash equilibrium for the proposed game is derived. It is shown that the equilibrium is one where the powers are signal-to-interference-plus-noise ratio-balanced with the minimum mean-square error (MMSE) detector as the receiver. In addition, this framework is used to study power-control games for the matched filter, the decorrelator, and the MMSE detector; and the receivers' performance is compared in terms of the utilities achieved at equilibrium (in bits/joule). The optimal cooperative solution is also discussed and compared with the noncooperative approach. Extensions of the results to the case of multiple receive antennas are also presented. In addition, an admission-control scheme based on maximizing the total utility in the network is proposed.
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paper_title: Energy-Efficient Resource Allocation in OFDM Systems With Distributed Antennas

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In this paper, we develop an energy-efficient resource-allocation scheme with proportional fairness for downlink multiuser orthogonal frequency-division multiplexing (OFDM) systems with distributed antennas. Our aim is to maximize energy efficiency (EE) under the constraints of the overall transmit power of each remote access unit (RAU), proportional fairness data rates, and bit error rates (BERs). Because of the nonconvex nature of the optimization problem, obtaining the optimal solution is extremely computationally complex. Therefore, we develop a low-complexity suboptimal algorithm, which separates subcarrier allocation and power allocation. For the low-complexity algorithm, we first allocate subcarriers by assuming equal power distribution. Then, by exploiting the properties of fractional programming, we transform the nonconvex optimization problem in fractional form into an equivalent optimization problem in subtractive form, which includes a tractable solution. Next, an optimal energy-efficient power-allocation algorithm is developed to maximize EE while maintaining proportional fairness. Through computer simulation, we demonstrate the effectiveness of the proposed low-complexity algorithm and illustrate the fundamental tradeoff between energy- and spectral-efficient transmission designs.
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paper_title: A game-theoretic approach to energy-efficient power control in multicarrier CDMA systems

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A game-theoretic model for studying power control in multicarrier code-division multiple-access systems is proposed. Power control is modeled as a noncooperative game in which each user decides how much power to transmit over each carrier to maximize its own utility. The utility function considered here measures the number of reliable bits transmitted over all the carriers per joule of energy consumed and is particularly suitable for networks where energy efficiency is important. The multidimensional nature of users' strategies and the nonquasi-concavity of the utility function make the multicarrier problem much more challenging than the single-carrier or throughput-based-utility case. It is shown that, for all linear receivers including the matched filter, the decorrelator, and the minimum-mean-square-error detector, a user's utility is maximized when the user transmits only on its "best" carrier. This is the carrier that requires the least amount of power to achieve a particular target signal-to-interference-plus-noise ratio at the output of the receiver. The existence and uniqueness of Nash equilibrium for the proposed power control game are studied. In particular, conditions are given that must be satisfied by the channel gains for a Nash equilibrium to exist, and the distribution of the users among the carriers at equilibrium is characterized. In addition, an iterative and distributed algorithm for reaching the equilibrium (when it exists) is presented. It is shown that the proposed approach results in significant improvements in the total utility achieved at equilibrium compared with a single-carrier system and also to a multicarrier system in which each user maximizes its utility over each carrier independently
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paper_title: Energy-efficient resource allocation in multi-cell OFDMA systems with limited backhaul capacity

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In this paper, resource allocation for energy efficient communication in multi-cell orthogonal frequency division multiple access (OFDMA) downlink networks with cooperative base stations (BSs) is studied. The considered problem is formulated as a non-convex optimization problem which takes into account the circuit power consumption, the limited backhaul capacity, and the minimum required data rate for joint BS zero-forcing beamforming (ZFBF) transmission. By exploiting the properties of fractional programming, the considered non-convex optimization problem in fractional form is transformed into an equivalent optimization problem in subtractive form, which enables the derivation of an efficient iterative resource allocation algorithm. For each iteration, the optimal power allocation solution is derived with a low complexity suboptimal subcarrier allocation policy for maximization of the energy efficiency of data transmission (bit/Joule delivered to the users). Simulation results illustrate that the proposed iterative resource allocation algorithm converges in a small number of iterations, and unveil the trade-off between energy efficiency and network capacity.
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paper_title: Coordinated Multicell Multiuser Precoding for Maximizing Weighted Sum Energy Efficiency

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Energy efficiency optimization of wireless systems has become urgently important due to its impact on the global carbon footprint. In this paper we investigate energy efficient multicell multiuser precoding design and consider a new criterion of weighted sum energy efficiency, which is defined as the weighted sum of the energy efficiencies of multiple cells. This objective is more general than the existing methods and can satisfy heterogeneous requirements from different kinds of cells, but it is hard to tackle due to its sum-of-ratio form. In order to address this non-convex problem, the user rate is first formulated as a polynomial optimization problem with the test conditional probabilities to be optimized. Based on that, the sum-of-ratio form of the energy efficient precoding problem is transformed into a parameterized polynomial form optimization problem, by which a solution in closed form is achieved through a two-layer optimization. We also show that the proposed iterative algorithm is guaranteed to converge. Numerical results are finally provided to confirm the effectiveness of our energy efficient beamforming algorithm. It is observed that in the low signal-to-noise ratio (SNR) region, the optimal energy efficiency and the optimal sum rate are simultaneously achieved by our algorithm; while in the middle-high SNR region, a certain performance loss in terms of the sum rate is suffered to guarantee the weighed sum energy efficiency.
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paper_title: Power Minimization Based Resource Allocation for Interference Mitigation in OFDMA Femtocell Networks

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With the introduction of femtocells, cellular networks are moving from the conventional centralized network architecture to a distributed one, where each network cell should make its own radio resource allocation decisions, while providing inter-cell interference mitigation. However, realizing such distributed network architecture is not a trivial task. In this paper, we first introduce a simple self-organization rule, based on minimizing cell transmit power, following which a distributed cellular network is able to converge into an efficient resource reuse pattern. Based on such self-organization rule and taking realistic resource allocation constraints into account, we also propose two novel resource allocation algorithms, being autonomous and coordinated, respectively. Performance of the proposed self-organization rule and resource allocation algorithms are evaluated using system-level simulations, and show that power efficiency is not necessarily in conflict with capacity improvements at the network level. The proposed resource allocation algorithms provide significant performance improvements in terms of user outages and network capacity over cutting-edge resource allocation algorithms proposed in the literature.
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paper_title: Energy Efficiency in Wireless Networks via Fractional Programming Theory

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This monograph presents a unified framework for energy efficiency maximization in wireless networks via fractional programming theory. The definition of energy efficiency is introduced, with reference to single-user and multi-user wireless networks, and it is observed how the problem of resource allocation for energy efficiency optimization is naturally cast as a fractional program. An extensive review of the state-of-the-art in energy efficiency optimization by fractional programming is provided, with reference to centralized and distributed resource allocation schemes. A solid background on fractional programming theory is provided. The key-notion of generalized concavity is presented and its strong connection with fractional functions described. A taxonomy of fractional problems is introduced, and for each class of fractional problem, general solution algorithms are described, discussing their complexity and convergence properties. The described theoretical and algorithmic framework is applied to solve energy efficiency maximization problems in practical wireless networks. A general system and signal model is developed which encompasses many relevant special cases, such as one-hop and two-hop heterogeneous networks, multi-cell networks, small-cell networks, device-to-device systems, cognitive radio systems, and hardware-impaired networks, wherein multiple-antennas and multiple subcarriers are possibly employed. Energy-efficient resource allocation algorithms are developed, considering both centralized, cooperative schemes, as well as distributed approaches for self-organizing networks. Finally, some remarks on future lines of research are given, stating some open problems that remain to be studied. It is shown how the described framework is general enough to be extended in these directions, proving useful in tackling future challenges that may arise in the design of energy-efficient future wireless networks.
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paper_title: Design of 3-Way Relay Channels for Throughput and Energy Efficiency.

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AbstractThroughput and energy efciency in 3-way relay channels are studied in this paper. Unlike previouscontributions, we consider a circular message exchange. First, an outer bound and achievable sum rateexpressions for different relaying protocols are derived for 3-way relay channels. The sum capacity ischaracterized for certain SNR regimes. Next, leveraging the derived achievable sum rate expressions,cooperative and competitive maximization of the energy efciency are considered. For the cooperativecase, both low-complexity and globally optimal algorithms for joint power allocation at the users and atthe relay are designed so as to maximize the system global energy efciency. For the competitive case, agame theoretic approach is taken, and it is shown that the best response dynamics is guaranteed to convergeto a Nash equilibrium. A power consumption model for mmWave board-to-board communications isdeveloped, and numerical results are provided to corroborate and provide insight on the theoreticalndings.Index TermsMulti-way networks, relay systems, energy efcienc y, green communications, resource allocation,fractional programming, monotonic optimization, game theory, 5G networks, mmWave communications,power control.
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paper_title: Energy-Efficient Power Control: A Look at 5G Wireless Technologies

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This paper develops power control algorithms for energy efficiency (EE) maximization (measured in bit/Joule) in wireless networks. Unlike previous related works, minimum-rate constraints are imposed and the signal-to-interference-plus-noise ratio takes a more general expression, which allows one to encompass some of the most promising 5G candidate technologies. Both network-centric and user-centric EE maximizations are considered. In the network-centric scenario, the maximization of the global EE and the minimum EE of the network is performed. Unlike previous contributions, we develop centralized algorithms that are guaranteed to converge, with affordable computational complexity, to a Karush–Kuhn–Tucker point of the considered non-convex optimization problems. Moreover, closed-form feasibility conditions are derived. In the user-centric scenario, game theory is used to study the equilibria of the network and to derive convergent power control algorithms, which can be implemented in a fully decentralized fashion. Both scenarios above are studied under the assumption that single or multiple resource blocks are employed for data transmission. Numerical results assess the performance of the proposed solutions, analyzing the impact of minimum-rate constraints, and comparing the network-centric and user-centric approaches.
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paper_title: Energy-Efficient Configuration of Spatial and Frequency Resources in MIMO-OFDMA Systems

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In this paper, we investigate adaptive configuration of spatial and frequency resources to maximize energy efficiency (EE) and reveal the relationship between the EE and the spectral efficiency (SE) in downlink multiple-input-multiple-output (MIMO) orthogonal frequency division multiple access (OFDMA) systems. We formulate the problem as minimizing the total power consumed at the base station under constraints on the ergodic capacities from multiple users, the total number of subcarriers, and the number of radio frequency (RF) chains. A three-step searching algorithm is developed to solve this problem. We then analyze the impact of spatial-frequency resources, overall SE requirement and user fairness on the SE-EE relationship. Analytical and simulation results show that increasing frequency resource is more efficient than increasing spatial resource to improve the SE-EE relationship as a whole. The EE increases with the SE when the frequency resource is not constrained to the maximum value, otherwise a tradeoff between the SE and the EE exists. Sacrificing the fairness among users in terms of ergodic capacities can enhance the SE-EE relationship. In general, the adaptive configuration of spatial and frequency resources outperforms the adaptive configuration of only spatial or frequency resource.
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paper_title: Energy-Efficient Scheduling and Power Allocation in Downlink OFDMA Networks With Base Station Coordination

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This paper addresses the problem of energy-efficient resource allocation in the downlink of a cellular OFDMA system. Three definitions of the energy efficiency are considered for system design, accounting for both the radiated and the circuit power. User scheduling and power allocation are optimized across a cluster of coordinated base stations with a constraint on the maximum transmit power (either per subcarrier or per base station). The asymptotic noise-limited regime is discussed as a special case. %The performance of both an isolated and a non-isolated cluster of coordinated base stations is examined in the numerical experiments. Results show that the maximization of the energy efficiency is approximately equivalent to the maximization of the spectral efficiency for small values of the maximum transmit power, while there is a wide range of values of the maximum transmit power for which a moderate reduction of the data rate provides a large saving in terms of dissipated energy. Also, the performance gap among the considered resource allocation strategies reduces as the out-of-cluster interference increases.
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paper_title: A Game-Theoretic Approach to Energy-Efficient Power Control and Receiver Design in Cognitive CDMA Wireless Networks

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The uplink of a multiuser cognitive radio network, wherein secondary users communicating with a secondary access point coexist with primary users communicating with a primary access point, is considered in this paper. Primary and secondary users' signals coexist in the same frequency band, and the transmit powers of the secondary users are constrained so that the interference from the whole secondary network to each primary user does not exceed a prescribed threshold. Given this constraint, a noncooperative power control game for maximum energy efficiency with a fairness constraint on the maximum received powers for the secondary users has been considered. The considered game is shown to admit a unique Nash equilibrium, also in the case in which energy efficiency is maximized with respect to both transmit power and choice of the linear uplink receiver. Based on large system analysis, a one-shot procedure for computing the users' transmit powers at the Nash equilibrium with no need for iteration among users is also derived. Numerical simulations confirm the theoretical results on the existence and uniqueness of the Nash equilibrium, confirm the effectiveness of the results obtained through the large system analysis, and show that secondary users have a beneficial impact on the whole network throughput, at the price of a moderate degradation in the performance of the primary users.
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paper_title: Transmitter Waveform and Widely Linear Receiver Design: Noncooperative Games for Wireless Multiple-Access Networks

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The issue of noncooperative transceiver optimization in the uplink of a multiuser wireless code division multiple access data network with widely linear detection at the receiver is considered. While previous work in this area has focused on a simple real signal model, in this paper, a baseband complex representation of the data is used so as to properly take into account the I and Q components of the received signal. For the case in which the received signal is improper, a widely linear reception structure, processing separately the data and their complex conjugates, is considered. Several noncooperative resource allocation games are considered for this new scenario, and the performance gains granted by the use of widely linear detection are assessed through theoretical analysis. Numerical results confirm the validity of the theoretical findings and show that exploiting the improper nature of the data in noncooperative resource allocation brings remarkable performance improvements in multiuser wireless systems.
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paper_title: A Novel Power Consumption Model for Effective Energy Efficiency in Wireless Networks

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Designing energy-efficient delay-aware communication networks have become an inevitable trend in 5G wireless networks. In this letter, we present an energy-efficient and delay-aware cross-layer resource allocation in SISO wireless systems. To achieve this goal, we apply the notion of effective energy efficiency (EEE), defined as the ratio of the system effective capacity (EC) over the total power consumption. Unlike previous works, we introduce a new average power consumption model which accounts for the data link layer, allowing for the probability of emptying the buffer during the transmission timeframe. This leads to a new definition of EEE, which results in better performance in terms of both EEE and EC.
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paper_title: Energy-Aware Competitive Power Control in Relay-Assisted Interference Wireless Networks

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Competitive power control for energy efficiency maximization in wireless interference networks is addressed, for the scenarios in which the users' SINR can be expressed as either (a) γ=(α p)/(φ p+ω), or (b) γ=(α p+β p^{2})/(φ p+ω), with p the user's transmit power. The considered SINR expressions naturally arise in relay-assisted systems. The energy efficiency is measured in bit/Joule and is defined as the ratio of a proper function of the SINR, divided by the consumed power. Unlike most previous related works, in the definition of the consumed power, not only the transmit power, but also the circuit power needed to operate the devices is accounted for. A non-cooperative game theoretic approach is employed and distributed power control algorithms are proposed. For both SINR expressions (a) and (b), it is shown that the competitive power allocation problem always admits a Nash equilibrium. Moreover, for the SINR (a), the equilibrium is also shown to be unique and the best-response dynamic is guaranteed to converge to such unique equilibrium. For the two-user case, the efficient computation of the Pareto frontier of the considered game is addressed, and, for benchmarking purposes, a social optimum solution with fairness constraint is derived.
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paper_title: Energy-Efficient Power Control of Cognitive Femto Users for 5G Communications

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We study the energy efficiency issue in 5G communications scenarios, where cognitive femtocells coexist with picocells operating at the same frequency bands. Optimal energy-efficient power allocation based on the sensing-based spectrum sharing (SBSS) is proposed for the uplink cognitive femto users operating in a multiuser MIMO mode. Both hard-decision and soft-decision schemes are considered for the SBSS. Different from the existing energy-efficient designs in multiuser scenarios, which consider system-wise energy efficiency, we consider user-wise energy efficiency and optimize them in a Pareto sense. To resolve the nonconvexity of the formulated optimization problem, we include an additional power constraint to convexify the problem without losing global optimality. Simulation results show that the proposed schemes significantly enhance the energy efficiency of the cognitive femto users compared with the existing spectral-efficient designs.
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paper_title: Energy-Aware and Rate-Aware Heuristic Beamforming in Downlink MIMO OFDMA Networks With Base-Station Coordination

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This paper addresses the problem of coordinated beamforming across a group of base stations (BSs) and frequency slots in the downlink of a multiple-input multiple-output (MIMO) orthogonal frequency-division multiple-access (OFDMA) cellular network. Three figures of merit are considered for system design under a per-BS power constraint: 1) the weighted sum of the rates (WSR) on the frequency slots of the coordinated BSs; 2) the global energy efficiency (GEE), defined as the ratio between the network sum rate and the corresponding consumed power; and 3) the weighted sum of the energy efficiencies (WSEE) on the frequency slots of the coordinated BSs. The Karush–Kuhn–Tucker (KKT) conditions of the considered optimization problems are first derived to gain insight into the structure of the optimal beamformers. Then, we propose a suboptimal design method that can be applied to all considered figures of merit. Numerical results are provided to assess the performance of the proposed beamforming strategies.
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paper_title: Energy-efficient MIMO underlay spectrum sharing with rate splitting

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This work studies energy efficiency (EE) of multiple-input and multiple-output (MIMO) underlay spectrum sharing, where rate splitting at the secondary transmitter and successive decoding at the secondary receiver is deployed when feasible. EE of the secondary transmission is optimized while satisfying the primary rate requirement and the secondary power constraint. EE is defined as the ratio of the achievable secondary rate and the secondary power consumption, including both the transmit power and the circuit power. Numerical results show that higher EE can be achieved at the cost of achievable rate compared with that of MIMO underlay spectrum sharing with rate optimization, and that rate splitting is beneficial in terms of EE.
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paper_title: Distributed Interference-Aware Energy-Efficient Power Optimization

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Power optimization techniques are becoming increasingly important in wireless system design since battery technology has not kept up with the demand of mobile devices. They are also critical to interference management in wireless systems because interference usually results from both aggressive spectral reuse and high power transmission and severely limits system performance. In this paper, we develop an energy-efficient power optimization scheme for interference-limited wireless communications. We consider both circuit and transmission powers and focus on energy efficiency over throughput. We first investigate a non-cooperative game for energy-efficient power optimization in frequency-selective channels and reveal the conditions of the existence and uniqueness of the equilibrium for this game. Most importantly, we discover a sufficient condition for generic multi-channel power control to have a unique equilibrium in frequency-selective channels. Then we study the tradeoff between energy efficiency and spectral efficiency and show by simulation results that the proposed scheme improves both energy efficiency and spectral efficiency in an interference-limited multi-cell cellular network.
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paper_title: Precoding for Full Duplex Multiuser MIMO Systems: Spectral and Energy Efficiency Maximization

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We consider data transmissions in a full duplex (FD) multiuser multiple-input multiple-output (MU-MIMO) system, where a base station (BS) bidirectionally communicates with multiple users in the downlink (DL) and uplink (UL) channels on the same system resources. The system model of consideration has been thought to be impractical due to the self-interference (SI) between transmit and receive antennas at the BS. Interestingly, recent advanced techniques in hardware design have demonstrated that the SI can be suppressed to a degree that possibly allows for FD transmission. This paper goes one step further in exploring the potential gains in terms of the spectral efficiency (SE) and energy efficiency (EE) that can be brought by the FD MU-MIMO model. Toward this end, we propose low-complexity designs for maximizing the SE and EE, and evaluate their performance numerically. For the SE maximization problem, we present an iterative design that obtains a locally optimal solution based on a sequential convex approximation method. In this way, the nonconvex precoder design problem is approximated by a convex program at each iteration. Then, we propose a numerical algorithm to solve the resulting convex program based on the alternating and dual decomposition approaches, where analytical expressions for precoders are derived. For the EE maximization problem, using the same method, we first transform it into a concave-convex fractional program, which then can be reformulated as a convex program using the parametric approach. We will show that the resulting problem can be solved similarly to the SE maximization problem. Numerical results demonstrate that, compared to a half duplex system, the FD system of interest with the proposed designs achieves a better SE and a slightly smaller EE when the SI is small.
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paper_title: Learning to Be Green: Robust Energy Efficiency Maximization in Dynamic MIMO–OFDM Systems

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In this paper, we examine the maximization of energy efficiency (EE) in next-generation multiuser MIMO–OFDM networks that vary dynamically over time—e.g., due to user mobility, fluctuations in the wireless medium, modulations in the users’ load, etc. Contrary to the static/stationary regime, the system may evolve in an arbitrary manner, so users must adjust “on the fly,” without being able to predict the state of the system in advance. To tackle these issues, we propose a simple and distributed online optimization policy that leads to no regret , i.e., it allows users to match (and typically outperform) even the best fixed transmit policy in hindsight, irrespective of how the system varies with time. Moreover, to account for the scarcity of perfect channel state information (CSI) in massive MIMO systems, we also study the algorithm’s robustness in the presence of measurement errors and observation noise. Importantly, the proposed policy retains its no-regret properties under very mild assumptions on the error statistics: on average, it enjoys the same performance guarantees as in the noiseless deterministic case. Our analysis is supplemented by extensive numerical simulations, which show that, in realistic network environments, users track their individually optimum transmit profile even under rapidly changing channel conditions, achieving gains of up to 600% in energy efficiency over uniform power allocation policies.
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paper_title: Framework for Link-Level Energy Efficiency Optimization with Informed Transmitter

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The dramatic increase of network infrastructure comes at the cost of rapidly increasing energy consumption, which makes optimization of energy efficiency (EE) an important topic. Since EE is often modeled as the ratio of rate to power, we present a mathematical framework called fractional programming that provides insight into this class of optimization problems, as well as algorithms for computing the solution. The main idea is that the objective function is transformed to a weighted sum of rate and power. A generic problem formulation for systems dissipating transmit-independent circuit power in addition to transmit-dependent power is presented. We show that a broad class of EE maximization problems can be solved efficiently, provided the rate is a concave function of the transmit power. We elaborate examples of various system models including time-varying parallel channels. Rate functions with an arbitrary discrete modulation scheme are also treated. The examples considered lead to water-filling solutions, but these are different from the dual problems of power minimization under rate constraints and rate maximization under power constraints, respectively, because the constraints need not be active. We also demonstrate that if the solution to a rate maximization problem is known, it can be utilized to reduce the EE problem into a one-dimensional convex problem.
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paper_title: Joint Receiver and Transmitter Optimization for Energy-Efficient CDMA Communications

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This paper focuses on the cross-layer issue of joint multiuser detection and resource allocation for energy efficiency in wireless code-division multiple-access (CDMA) networks. In particular, assuming that a linear multiuser detector is adopted in the uplink receiver, the situation considered is that in which each terminal is allowed to vary its transmit power, spreading code, and uplink receiver in order to maximize its own utility, which is defined as the ratio of data throughput to transmit power. Applying a game-theoretic formulation, a non-cooperative game for utility maximization is formulated, and it is proved that a unique Nash equilibrium exists, which, under certain conditions, is also Pareto-optimal. Theoretical results concerning the relationship between the problems of signal-to-interference-plus noise ratio (SINR) maximization and mean-square error (MSE) minimization are given, and, by applying the tools of large system analysis, a new distributed power control algorithm is implemented, based on very little prior information about the user of interest. The utility profile achieved by the active users in a large CDMA system is also computed, and, moreover, the centralized socially optimal solution is analyzed. Considerations concerning the extension of the proposed framework to a multi-cell scenario are also briefly detailed. Simulation results confirm that the proposed non-cooperative game largely outperforms competing alternatives, and that it exhibits negligible performance loss with respect to the socially optimal solution, and only in the case in which the number of users exceeds the processing gain. Finally, results also show an excellent agreement between the theoretical closed-form formulas based on large system analysis and the outcome of numerical experiments.
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paper_title: Energy Efficiency Optimization for MIMO Broadcast Channels

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Characterizing the fundamental energy efficiency (EE) limits of MIMO broadcast channels (BC) is significant for the development of green wireless communications. We address the EE optimization problem for MIMO-BC in this paper and consider a practical power model, i.e., taking into account a transmit independent power which is related to the number of active transmit antennas. Under this setup, we propose a new optimization approach, in which the transmit covariance is optimized under fixed active transmit antenna sets, and then active transmit antenna selection (ATAS) is utilized. During the transmit covariance optimization, we propose a globally optimal energy efficient iterative water-filling scheme through solving a series of concave-convex fractional programs based on the block-coordinate ascent algorithm. After that, ATAS is employed to determine the active transmit antenna set. Since activating more transmit antennas can achieve higher sum-rate but at the cost of larger transmit independent power consumption, there exists a tradeoff between the sum-rate gain and the power consumption. Here ATAS can explore the optimal tradeoff curve and thus further improve the EE. Optimal exhaustive search and low-complexity norm based ATAS schemes are developed. Through simulations, we discuss the effect of different parameters on the EE of the MIMO-BC.
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paper_title: A Game-Theoretic Approach to Energy-Efficient Modulation in CDMA Networks with Delay QoS Constraints

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A game-theoretic framework is used to study the effect of constellation size on the energy efficiency of wireless networks for M-QAM modulation. A non-cooperative game is proposed in which each user seeks to choose its transmit power (and possibly transmit symbol rate) as well as the constellation size in order to maximize its own utility while satisfying its delay quality-of-service (QoS) constraint. The utility function used here measures the number of reliable bits transmitted per joule of energy consumed, and is particularly suitable for energy-constrained networks. The best-response strategies and Nash equilibrium solution for the proposed game are derived. It is shown that in order to maximize its utility (in bits per joule), a user must choose the lowest constellation size that can accommodate the user's delay constraint. This strategy is different from one that would maximize spectral efficiency. Using this framework, the tradeoffs among energy efficiency, delay, throughput and constellation size are also studied and quantified. In addition, the effect of trellis-coded modulation on energy efficiency is discussed.
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paper_title: Energy-Efficient Power Control in Impulse Radio UWB Wireless Networks

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In this paper, a game-theoretic model for studying power control for wireless data networks in frequency-selective multipath environments is analyzed. The uplink of an impulse-radio ultrawideband system is considered. The effects of self-interference and multiple-access interference on the performance of generic Rake receivers are investigated for synchronous systems. Focusing on energy efficiency, a noncooperative game is proposed in which users in the network are allowed to choose their transmit powers to maximize their own utilities, and the Nash equilibrium for the proposed game is derived. It is shown that, due to the frequency selective multipath, the noncooperative solution is achieved at different signal-to-interference-plus-noise ratios, depending on the channel realization and the type of Rake receiver employed. A large-system analysis is performed to derive explicit expressions for the achieved utilities. The Pareto-optimal (cooperative) solution is also discussed and compared with the noncooperative approach.
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paper_title: Distributed Energy-Efficient Power Optimization for CoMP Systems With Max-Min Fairness

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This letter considers the power optimization problem for downlink transmission in coordinated multi-point (CoMP) systems. We aim to maximize the minimum weighted energy efficiency (EE) with QoS constraint and limited intercell coordination. The established optimization problem is converted to the standard form of max-min fractional programming problem first. Then we discuss feasibility of the Dual Dinkelbach-type Algorithm (DDA). A distributed algorithm is proposed to solve the subproblem in DDA with limited intercell coordination, where only a small number of positive scalars are shared between base stations. Simulation results show that the proposed algorithm outperforms previous schemes in terms of both the minimum EE of all the BSs' EE and fairness.
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paper_title: Resource Allocation for Power Minimization in the Downlink of THP-Based Spatial Multiplexing MIMO-OFDMA Systems

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In this paper, we deal with resource allocation in the downlink of spatial multiplexing multiple-input–multiple-output (MIMO)-orthogonal frequency-division multiple-access (OFDMA) systems. In particular, we concentrate on the problem of jointly optimizing the transmit and receive processing matrices, the channel assignment, and the power allocation with the objective of minimizing the total power consumption while satisfying different quality-of-service (QoS) requirements. A layered architecture is used in which users are first partitioned in different groups on the basis of their channel quality, and then channel assignment and transceiver design are sequentially addressed starting from the group of users with most adverse channel conditions. The multiuser interference among users belonging to different groups is removed at the base station (BS) using a Tomlinson–Harashima precoder operating at user level. Numerical results are used to highlight the effectiveness of the proposed solution and to make comparisons with existing alternatives.
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paper_title: Energy Efficiency Optimization in Licensed-Assisted Access

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To improve system capacity, licensed-assisted access (LAA) has been proposed for long-term evolution (LTE) systems to use unlicensed bands. However, the energy efficiency (EE) of the LTE system may be degraded by LAA since unlicensed bands are generally less energy-efficient than licensed bands. In this paper, we investigate the EE optimization of LAA systems. We first develop a criterion to determine whether unlicensed bands can be leveraged to improve the EE of LAA systems. We prove that unlicensed bands can be used to improve the EE only when the allocated licensed resource blocks (RBs) are not enough. We then investigate joint licensed and unlicensed RB allocation to maximize the EE of each small cell base station (SBS) in a multi-SBS scenario, taking into account fair resource sharing between LTE and WiFi networks. The complete Pareto optimal EE set can be obtained by the weighted Tchebycheff method. We also develop an algorithm to provide fair EE among different SBSs based on the Nash bargaining solution. Numerical results are presented to confirm our analysis and to demonstrate the effectiveness of the proposed algorithms.
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paper_title: Energy-Efficient Cell Activation, User Association, and Spectrum Allocation in Heterogeneous Networks

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Next generation (5G) cellular networks are expected to be supported by an extensive infrastructure with many-fold increase in the number of cells per unit area compared to today. The total energy consumption of base transceiver stations (BTSs) is an important issue for both economic and environmental reasons. In this paper, an optimization-based framework is proposed for energy-efficient global radio resource management in heterogeneous wireless networks. Specifically, with stochastic arrivals of known rates intended for users, the smallest set of BTSs is activated with jointly optimized user association and spectrum allocation to stabilize the network. The average delay is subsequently minimized. The scheme can be carried out periodically on a relatively slow timescale to adapt to aggregate traffic variations and average channel conditions. Numerical results show that the proposed scheme significantly reduces energy consumption and increases quality of service compared to existing schemes.
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paper_title: Massive MIMO for Next Generation Wireless Systems

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Multi-user MIMO offers big advantages over conventional point-to-point MIMO: it works with cheap single-antenna terminals, a rich scattering environment is not required, and resource allocation is simplified because every active terminal utilizes all of the time-frequency bins. However, multi-user MIMO, as originally envisioned, with roughly equal numbers of service antennas and terminals and frequency-division duplex operation, is not a scalable technology. Massive MIMO (also known as large-scale antenna systems, very large MIMO, hyper MIMO, full-dimension MIMO, and ARGOS) makes a clean break with current practice through the use of a large excess of service antennas over active terminals and time-division duplex operation. Extra antennas help by focusing energy into ever smaller regions of space to bring huge improvements in throughput and radiated energy efficiency. Other benefits of massive MIMO include extensive use of inexpensive low-power components, reduced latency, simplification of the MAC layer, and robustness against intentional jamming. The anticipated throughput depends on the propagation environment providing asymptotically orthogonal channels to the terminals, but so far experiments have not disclosed any limitations in this regard. While massive MIMO renders many traditional research problems irrelevant, it uncovers entirely new problems that urgently need attention: the challenge of making many low-cost low-precision components that work effectively together, acquisition and synchronization for newly joined terminals, the exploitation of extra degrees of freedom provided by the excess of service antennas, reducing internal power consumption to achieve total energy efficiency reductions, and finding new deployment scenarios. This article presents an overview of the massive MIMO concept and contemporary research on the topic.
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paper_title: Scaling up MIMO: Opportunities and challenges with very large arrays

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Presents a list of articles published by the IEEE Signal Processing Society (SPS) that ranked among the top 100 most downloaded IEEE Xplore articles.
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paper_title: Energy Group-Buying with Loading Sharing for Green Cellular Networks

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In the emerging hybrid electricity market, mobile network operators (MNOs) of cellular networks can make day-ahead energy purchase commitments at low prices and real-time flexible energy purchase at high prices. To minimize electricity bills, it is essential for MNOs to jointly optimize the day-ahead and real-time energy purchase based on their time-varying wireless traffic load. In this paper, we consider two different MNOs coexisting in the same area, and exploit their collaboration in both energy purchase and wireless load sharing for energy cost saving. Specifically, we propose a new approach named energy group buying with load sharing, in which the two MNOs are aggregated as a single group to make the day-ahead and real-time energy purchase, and their base stations (BSs) share the wireless traffic to maximally turn lightly-loaded BSs into sleep mode. When the two MNOs belong to the same entity and aim to minimize their total energy cost, we use the two-stage stochastic programming to obtain the optimal day-ahead and real-time energy group buying jointly with wireless load sharing. When the two MNOs belong to different entities and are self-interested in minimizing their individual energy costs, we propose a novel repeated Nash bargaining scheme for them to negotiate and share their energy costs under energy group buying and load sharing. Our proposed repeated Nash bargaining scheme is shown to achieve Pareto-optimal and fair energy cost reductions for both MNOs.
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paper_title: Performance of Conjugate and Zero-Forcing Beamforming in Large-Scale Antenna Systems

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Large-Scale Antenna Systems (LSAS) is a form of multi-user MIMO technology in which unprecedented numbers of antennas serve a significantly smaller number of autonomous terminals. We compare the two most prominent linear pre-coders, conjugate beamforming and zero-forcing, with respect to net spectral-efficiency and radiated energy-efficiency in a simplified single-cell scenario where propagation is governed by independent Rayleigh fading, and where channel-state information (CSI) acquisition and data transmission are both performed during a short coherence interval. An effective-noise analysis of the pre-coded forward channel yields explicit lower bounds on net capacity which account for CSI acquisition overhead and errors as well as the sub-optimality of the pre-coders. In turn the bounds generate trade-off curves between radiated energy-efficiency and net spectral-efficiency. For high spectral-efficiency and low energy-efficiency zero-forcing outperforms conjugate beamforming, while at low spectral-efficiency and high energy-efficiency the opposite holds. Surprisingly, in an optimized system, the total LSAS-critical computational burden of conjugate beamforming may be greater than that of zero-forcing. Conjugate beamforming may still be preferable to zero-forcing because of its greater robustness, and because conjugate beamforming lends itself to a de-centralized architecture and de-centralized signal processing.
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paper_title: Energy-Efficient Power Control: A Look at 5G Wireless Technologies

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This paper develops power control algorithms for energy efficiency (EE) maximization (measured in bit/Joule) in wireless networks. Unlike previous related works, minimum-rate constraints are imposed and the signal-to-interference-plus-noise ratio takes a more general expression, which allows one to encompass some of the most promising 5G candidate technologies. Both network-centric and user-centric EE maximizations are considered. In the network-centric scenario, the maximization of the global EE and the minimum EE of the network is performed. Unlike previous contributions, we develop centralized algorithms that are guaranteed to converge, with affordable computational complexity, to a Karush–Kuhn–Tucker point of the considered non-convex optimization problems. Moreover, closed-form feasibility conditions are derived. In the user-centric scenario, game theory is used to study the equilibria of the network and to derive convergent power control algorithms, which can be implemented in a fully decentralized fashion. Both scenarios above are studied under the assumption that single or multiple resource blocks are employed for data transmission. Numerical results assess the performance of the proposed solutions, analyzing the impact of minimum-rate constraints, and comparing the network-centric and user-centric approaches.
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paper_title: Massive MIMO in the UL/DL of Cellular Networks: How Many Antennas Do We Need?

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We consider the uplink (UL) and downlink (DL) of non-cooperative multi-cellular time-division duplexing (TDD) systems, assuming that the number N of antennas per base station (BS) and the number K of user terminals (UTs) per cell are large. Our system model accounts for channel estimation, pilot contamination, and an arbitrary path loss and antenna correlation for each link. We derive approximations of achievable rates with several linear precoders and detectors which are proven to be asymptotically tight, but accurate for realistic system dimensions, as shown by simulations. It is known from previous work assuming uncorrelated channels, that as N→∞ while K is fixed, the system performance is limited by pilot contamination, the simplest precoders/detectors, i.e., eigenbeamforming (BF) and matched filter (MF), are optimal, and the transmit power can be made arbitrarily small. We analyze to which extent these conclusions hold in the more realistic setting where N is not extremely large compared to K. In particular, we derive how many antennas per UT are needed to achieve η% of the ultimate performance limit with infinitely many antennas and how many more antennas are needed with MF and BF to achieve the performance of minimum mean-square error (MMSE) detection and regularized zero-forcing (RZF), respectively.
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paper_title: Energy and Spectral Efficiency of Very Large Multiuser MIMO Systems

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A multiplicity of autonomous terminals simultaneously transmits data streams to a compact array of antennas. The array uses imperfect channel-state information derived from transmitted pilots to extract the individual data streams. The power radiated by the terminals can be made inversely proportional to the square-root of the number of base station antennas with no reduction in performance. In contrast if perfect channel-state information were available the power could be made inversely proportional to the number of antennas. Lower capacity bounds for maximum-ratio combining (MRC), zero-forcing (ZF) and minimum mean-square error (MMSE) detection are derived. An MRC receiver normally performs worse than ZF and MMSE. However as power levels are reduced, the cross-talk introduced by the inferior maximum-ratio receiver eventually falls below the noise level and this simple receiver becomes a viable option. The tradeoff between the energy efficiency (as measured in bits/J) and spectral efficiency (as measured in bits/channel use/terminal) is quantified for a channel model that includes small-scale fading but not large-scale fading. It is shown that the use of moderately large antenna arrays can improve the spectral and energy efficiency with orders of magnitude compared to a single-antenna system.
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paper_title: Energy Efficient Heterogeneous Cellular Networks

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With the exponential increase in mobile internet traffic driven by a new generation of wireless devices, future cellular networks face a great challenge to meet this overwhelming demand of network capacity. At the same time, the demand for higher data rates and the ever-increasing number of wireless users led to rapid increases in power consumption and operating cost of cellular networks. One potential solution to address these issues is to overlay small cell networks with macrocell networks as a means to provide higher network capacity and better coverage. However, the dense and random deployment of small cells and their uncoordinated operation raise important questions about the energy efficiency implications of such multi-tier networks. Another technique to improve energy efficiency in cellular networks is to introduce active/sleep (on/off) modes in macrocell base stations. In this paper, we investigate the design and the associated tradeoffs of energy efficient cellular networks through the deployment of sleeping strategies and small cells. Using a stochastic geometry based model, we derive the success probability and energy efficiency in homogeneous macrocell (single-tier) and heterogeneous K-tier wireless networks under different sleeping policies. In addition, we formulate the power consumption minimization and energy efficiency maximization problems, and determine the optimal operating regimes for macrocell base stations. Numerical results confirm the effectiveness of switching off base stations in homogeneous macrocell networks. Nevertheless, the gains in terms of energy efficiency depend on the type of sleeping strategy used. In addition, the deployment of small cells generally leads to higher energy efficiency but this gain saturates as the density of small cells increases. In a nutshell, our proposed framework provides an essential understanding on the deployment of future green heterogeneous networks.
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paper_title: Optimal Design of Energy-Efficient Multi-User MIMO Systems: Is Massive MIMO the Answer?

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Assume that a multi-user multiple-input multiple-output (MIMO) system is designed from scratch to uniformly cover a given area with maximal energy efficiency (EE). What are the optimal number of antennas, active users, and transmit power? The aim of this paper is to answer this fundamental question. We consider jointly the uplink and downlink with different processing schemes at the base station and propose a new realistic power consumption model that reveals how the above parameters affect the EE. Closed-form expressions for the EE-optimal value of each parameter, when the other two are fixed, are provided for zero-forcing (ZF) processing in single-cell scenarios. These expressions prove how the parameters interact. For example, in sharp contrast to common belief, the transmit power is found to increase (not to decrease) with the number of antennas. This implies that energy-efficient systems can operate in high signal-to-noise ratio regimes in which interference-suppressing signal processing is mandatory. Numerical and analytical results show that the maximal EE is achieved by a massive MIMO setup wherein hundreds of antennas are deployed to serve a relatively large number of users using ZF processing. The numerical results show the same behavior under imperfect channel state information and in symmetric multi-cell scenarios.
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paper_title: Spectral and Energy Efficiency of Multipair Two-Way Full-Duplex Relay Systems With Massive MIMO

paper_content:

In this paper, we consider a multipair amplify-and-forward two-way relay channel, where multiple pairs of full-duplex users exchange information through a full-duplex relay with massive antennas. For improving the energy efficiency, four typical power-scaling schemes are proposed based on the maximum-ratio combining/maximum-ratio transmission (MRC/MRT) and zero-forcing reception/zero-forcing transmission (ZFR/ZFT) at the relay. When the number of relay antennas tends to infinity, we quantify the asymptotic spectral efficiencies and energy efficiencies for the proposed power-scaling schemes. We show that the loop interference can be reduced by decreasing the transmit power under massive relay antennas. Besides, the inter-pair interference and inter-user interference in such systems can also be eliminated in large number of antennas. Moreover, we analytically compare the performance between MRC/MRT and ZFR/ZFT, and describe the impact of the number of user pairs on the spectral efficiency. We also evaluate the energy efficiency performance based on the practical power consumption model, and depict the impact of the relay antenna number on the energy efficiencies for the proposed schemes. Furthermore, we provide the available regions where full-duplex systems can outperform half-duplex systems. Finally, we show that the proposed schemes achieve good performance tradeoffs between the spectral efficiency and the energy efficiency.
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paper_title: Noncooperative Cellular Wireless with Unlimited Numbers of Base Station Antennas

paper_content:

A cellular base station serves a multiplicity of single-antenna terminals over the same time-frequency interval. Time-division duplex operation combined with reverse-link pilots enables the base station to estimate the reciprocal forward- and reverse-link channels. The conjugate-transpose of the channel estimates are used as a linear precoder and combiner respectively on the forward and reverse links. Propagation, unknown to both terminals and base station, comprises fast fading, log-normal shadow fading, and geometric attenuation. In the limit of an infinite number of antennas a complete multi-cellular analysis, which accounts for inter-cellular interference and the overhead and errors associated with channel-state information, yields a number of mathematically exact conclusions and points to a desirable direction towards which cellular wireless could evolve. In particular the effects of uncorrelated noise and fast fading vanish, throughput and the number of terminals are independent of the size of the cells, spectral efficiency is independent of bandwidth, and the required transmitted energy per bit vanishes. The only remaining impairment is inter-cellular interference caused by re-use of the pilot sequences in other cells (pilot contamination) which does not vanish with unlimited number of antennas.
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paper_title: From Immune Cells to Self-Organizing Ultra-Dense Small Cell Networks

paper_content:

In order to cope with the wireless traffic demand explosion within the next decade, operators are underlying their macrocellular networks with low power base stations in a more dense manner. Such networks are typically referred to as heterogeneous or ultra-dense small cell networks, and their deployment entails a number of challenges in terms of backhauling, capacity provision, and dynamics in spatio-temporally fluctuating traffic load. Self-organizing network (SON) solutions have been defined to overcome these challenges. Since self-organization occurs in a plethora of biological systems, we identify the design principles of immune system self-regulation and draw analogies with respect to ultra-dense small cell networks. In particular, we develop a mathematical model of an artificial immune system (AIS) that autonomously activates or deactivates small cells in response to the local traffic demand. The main goal of the proposed AIS-based SON approach is the enhancement of energy efficiency and improvement of cell-edge throughput. As a proof of principle, system level simulations are carried out in which the bio-inspired algorithm is evaluated for various parameter settings, such as the speed of small cell activation and the delay of deactivation. Analysis using spatio-temporally varying traffic exhibiting uncertainty through geo-location demonstrates the robustness of the AIS-based SON approach proposed.
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paper_title: Deploying Dense Networks for Maximal Energy Efficiency: Small Cells Meet Massive MIMO

paper_content:

What would a cellular network designed for maximal energy efficiency look like? To answer this fundamental question, tools from stochastic geometry are used in this paper to model future cellular networks and obtain a new lower bound on the average uplink spectral efficiency. This enables us to formulate a tractable uplink energy efficiency (EE) maximization problem and solve it analytically with respect to the density of base stations (BSs), the transmit power levels, the number of BS antennas and users per cell, and the pilot reuse factor. The closed-form expressions obtained from this general EE maximization framework provide valuable insights on the interplay between the optimization variables, hardware characteristics, and propagation environment. Small cells are proved to give high EE, but the EE improvement saturates quickly with the BS density. Interestingly, the maximal EE is achieved by also equipping the BSs with multiple antennas and operate in a “massive MIMO” fashion, where the array gain from coherent detection mitigates interference and the multiplexing of many users reduces the energy cost per user.
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paper_title: Energy-Per-Bit Minimized Radio Resource Allocation in Heterogeneous Networks

paper_content:

In this paper, we present an energy-per-bit minimized radio resource allocation scheme in heterogeneous networks equipped with multi-homing capability, simultaneously connecting to different wireless interfaces. Specifically, we formulate an optimization problem related to minimization of energy-per-bit which takes a form of nonlinear fractional programming. Then we derive a parametric optimization problem out of that fractional programming and solve the original problem by using a double-loop iteration method. In each iteration, we derive the optimal resource allocation policy by applying Lagrangian duality and an efficient dual update method. In addition, we present suboptimal resource allocation algorithms using the properties of the optimal resource allocation policy. Numerical results reveal that the optimal allocation algorithm improves energy efficiency significantly over the existing resource allocation algorithms designed for homogeneous networks and its performance is superior to suboptimal algorithms in reducing energy consumption as well as in enhancing network energy efficiency.
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paper_title: Massive MIMO Systems with Non-Ideal Hardware: Energy Efficiency, Estimation, and Capacity Limits

paper_content:

The use of large-scale antenna arrays can bring substantial improvements in energy and/or spectral efficiency to wireless systems due to the greatly improved spatial resolution and array gain. Recent works in the field of massive multiple-input multiple-output (MIMO) show that the user channels decorrelate when the number of antennas at the base stations (BSs) increases, thus strong signal gains are achievable with little interuser interference. Since these results rely on asymptotics, it is important to investigate whether the conventional system models are reasonable in this asymptotic regime. This paper considers a new system model that incorporates general transceiver hardware impairments at both the BSs (equipped with large antenna arrays) and the single-antenna user equipments (UEs). As opposed to the conventional case of ideal hardware, we show that hardware impairments create finite ceilings on the channel estimation accuracy and on the downlink/uplink capacity of each UE. Surprisingly, the capacity is mainly limited by the hardware at the UE, while the impact of impairments in the large-scale arrays vanishes asymptotically and interuser interference (in particular, pilot contamination) becomes negligible. Furthermore, we prove that the huge degrees of freedom offered by massive MIMO can be used to reduce the transmit power and/or to tolerate larger hardware impairments, which allows for the use of inexpensive and energy-efficient antenna elements.
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paper_title: Joint Design of Radio and Transport for Green Residential Access Networks

paper_content:

Mobile networks are the largest contributor to the carbon footprint of the telecom sector and their contribution is expected to rapidly increase in the future due to the foreseen traffic growth. Therefore, there is an increasing urgency in the definition of green mobile network deployment strategies. This paper proposes a four-step design and power assessment methodology for mobile networks, taking into consideration both radio and transport segments. A number of mobile network deployment architectures for urban residential areas based on different radio (i.e., macro base station, distributed indoor radio, femto cell) and transport (i.e., microwave, copper, optical fiber) technologies are proposed and evaluated to identify the most energy efficient solution. The results show that with low traffic the conventional macro base station deployment with microwave based backhaul is the best option. However, with higher traffic values heterogeneous networks with macro base stations and indoor small cells are more energy efficient. The best small cell solution highly depends on the transport network architecture. In particular, our results show that a femto cell based deployment with optical fiber backhaul is the most energy efficient, even if a distributed indoor radio architecture (DRA) deployment with fiber fronthaul is also a competitive approach.
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paper_title: Seven ways that HetNets are a cellular paradigm shift

paper_content:

Imagine a world with more base stations than cell phones: this is where cellular technology is headed in 10-20 years. This mega-trend requires many fundamental differences in visualizing, modeling, analyzing, simulating, and designing cellular networks vs. the current textbook approach. In this article, the most important shifts are distilled down to seven key factors, with the implications described and new models and techniques proposed for some, while others are ripe areas for future exploration.
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paper_title: Optimal Combination of Base Station Densities for Energy-Efficient Two-Tier Heterogeneous Cellular Networks

paper_content:

In this paper, the optimal BS (Base Station) density for both homogeneous and heterogeneous cellular networks to minimize network energy cost is analyzed with stochastic geometry theory. For homogeneous cellular networks, both upper and lower bounds of the optimal BS density are derived. For heterogeneous cellular networks, our analysis reveals the best type of BSs to be deployed for capacity extension, or to be switched off for energy saving. Specifically, if the ratio between the micro BS cost and the macro BS cost is lower than a threshold, which is a function of path loss and their transmit power, then the optimal strategy is to deploy micro BSs for capacity extension or to switch off macro BSs (if possible) for energy saving with higher priority. Otherwise, the optimal strategy is the opposite. The optimal combination of macro and micro BS densities can be calculated numerically through our analysis, or alternatively be conservatively approximated with a closed-form solution. Based on the parameters from EARTH, numerical results show that in the dense urban scenario, compared to the traditional macro-only homogeneous cellular network with no BS sleeping, deploying micro BSs can reduce about 40% of the total energy cost, and further reduce up to 35% with BS sleeping capability.
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paper_title: What Will 5G Be?

paper_content:

What will 5G be? What it will not be is an incremental advance on 4G. The previous four generations of cellular technology have each been a major paradigm shift that has broken backward compatibility. Indeed, 5G will need to be a paradigm shift that includes very high carrier frequencies with massive bandwidths, extreme base station and device densities, and unprecedented numbers of antennas. However, unlike the previous four generations, it will also be highly integrative: tying any new 5G air interface and spectrum together with LTE and WiFi to provide universal high-rate coverage and a seamless user experience. To support this, the core network will also have to reach unprecedented levels of flexibility and intelligence, spectrum regulation will need to be rethought and improved, and energy and cost efficiencies will become even more critical considerations. This paper discusses all of these topics, identifying key challenges for future research and preliminary 5G standardization activities, while providing a comprehensive overview of the current literature, and in particular of the papers appearing in this special issue.
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paper_title: Transmission capacity of wireless networks

paper_content:

Transmission capacity (TC) is a performance metric for wireless networks that measures the spatial intensity of successful transmissions per unit area, subject to a constraint on the permissible outage probability (where outage occurs when the SINR at a receiver is below a threshold). This volume gives a unified treatment of the TC framework that has been developed by the authors and their collaborators over the past decade. The mathematical framework underlying the analysis (reviewed in Ch. 2) is stochastic geometry: Poisson point processes model the locations of interferers, and (stable) shot noise processes represent the aggregate interference seen at a receiver. Ch. 3 presents TC results (exact, asymptotic, and bounds) on a simple model in order to illustrate a key strength of the framework: analytical tractability yields explicit performance dependence upon key model parameters. Ch. 4 presents enhancements to this basic model --- channel fading, variable link distances, and multi-hop. Ch. 5 presents four network design case studies well-suited to TC: i) spectrum management, ii) interference cancellation, iii) signal threshold transmission scheduling, and iv) power control. Ch. 6 studies the TC when nodes have multiple antennas, which provides a contrast vs. classical results that ignore interference.
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paper_title: Random Matrix Methods for Wireless Communications

paper_content:

Blending theoretical results with practical applications, this book provides an introduction to random matrix theory and shows how it can be used to tackle a variety of problems in wireless communications. The Stieltjes transform method, free probability theory, combinatoric approaches, deterministic equivalents and spectral analysis methods for statistical inference are all covered from a unique engineering perspective. Detailed mathematical derivations are presented throughout, with thorough explanation of the key results and all fundamental lemmas required for the reader to derive similar calculus on their own. These core theoretical concepts are then applied to a wide range of real-world problems in signal processing and wireless communications, including performance analysis of CDMA, MIMO and multi-cell networks, as well as signal detection and estimation in cognitive radio networks. The rigorous yet intuitive style helps demonstrate to students and researchers alike how to choose the correct approach for obtaining mathematically accurate results.
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paper_title: Energy-Efficient Hybrid Analog and Digital Precoding for MmWave MIMO Systems With Large Antenna Arrays

paper_content:

Millimeter wave (mmWave) MIMO will likely use hybrid analog and digital precoding, which uses a small number of RF chains to reduce the energy consumption associated with mixed signal components like analog-to-digital components not to mention baseband processing complexity. However, most hybrid precoding techniques consider a fully connected architecture requiring a large number of phase shifters, which is also energy-intensive. In this paper, we focus on the more energy-efficient hybrid precoding with subconnected architecture, and propose a successive interference cancelation (SIC)-based hybrid precoding with near-optimal performance and low complexity. Inspired by the idea of SIC for multiuser signal detection, we first propose to decompose the total achievable rate optimization problem with nonconvex constraints into a series of simple subrate optimization problems, each of which only considers one subantenna array. Then, we prove that maximizing the achievable subrate of each subantenna array is equivalent to simply seeking a precoding vector sufficiently close (in terms of Euclidean distance) to the unconstrained optimal solution. Finally, we propose a low-complexity algorithm to realize SIC-based hybrid precoding, which can avoid the need for the singular value decomposition (SVD) and matrix inversion. Complexity evaluation shows that the complexity of SIC-based hybrid precoding is only about 10% as complex as that of the recently proposed spatially sparse precoding in typical mmWave MIMO systems. Simulation results verify that SIC-based hybrid precoding is near-optimal and enjoys higher energy efficiency than the spatially sparse precoding and the fully digital precoding.
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paper_title: Device-to-device communication in 5G cellular networks: challenges, solutions, and future directions

paper_content:

In a conventional cellular system, devices are not allowed to directly communicate with each other in the licensed cellular bandwidth and all communications take place through the base stations. In this article, we envision a two-tier cellular network that involves a macrocell tier (i.e., BS-to-device communications) and a device tier (i.e., device-to-device communications). Device terminal relaying makes it possible for devices in a network to function as transmission relays for each other and realize a massive ad hoc mesh network. This is obviously a dramatic departure from the conventional cellular architecture and brings unique technical challenges. In such a two-tier cellular system, since the user data is routed through other users? devices, security must be maintained for privacy. To ensure minimal impact on the performance of existing macrocell BSs, the two-tier network needs to be designed with smart interference management strategies and appropriate resource allocation schemes. Furthermore, novel pricing models should be designed to tempt devices to participate in this type of communication. Our article provides an overview of these major challenges in two-tier networks and proposes some pricing schemes for different types of device relaying.
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paper_title: Wireless Device-to-Device Caching Networks: Basic Principles and System Performance

paper_content:

As wireless video is the fastest growing form of data traffic, methods for spectrally efficient on-demand wireless video streaming are essential to both service providers and users. A key property of video on-demand is the asynchronous content reuse , such that a few popular files account for a large part of the traffic but are viewed by users at different times. Caching of content on wireless devices in conjunction with device-to-device (D2D) communications allows to exploit this property, and provide a network throughput that is significantly in excess of both the conventional approach of unicasting from cellular base stations and the traditional D2D networks for “regular” data traffic. This paper presents in a tutorial and concise form some recent results on the throughput scaling laws of wireless networks with caching and asynchronous content reuse, contrasting the D2D approach with other alternative approaches such as conventional unicasting, harmonic broadcasting , and a novel coded multicasting approach based on caching in the user devices and network-coded transmission from the cellular base station only. Somehow surprisingly, the D2D scheme with spatial reuse and simple decentralized random caching achieves the same near-optimal throughput scaling law as coded multicasting. Both schemes achieve an unbounded throughput gain (in terms of scaling law) with respect to conventional unicasting and harmonic broadcasting, in the relevant regime where the number of video files in the library is smaller than the total size of the distributed cache capacity in the network. To better understand the relative merits of these competing approaches, we consider a holistic D2D system design incorporating traditional microwave (2 GHz) and millimeter-wave (mm-wave) D2D links; the direct connections to the base station can be used to provide those rare video requests that cannot be found in local caches. We provide extensive simulation results under a variety of system settings and compare our scheme with the systems that exploit transmission from the base station only. We show that, also in realistic conditions and nonasymptotic regimes, the proposed D2D approach offers very significant throughput gains.
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paper_title: Traffic off-balancing algorithm for energy efficient networks

paper_content:

Physical layer of high-end network system uses multiple interface arrays. Under the load-balancing perspective, light load can be distributed to multiple interfaces. However, it can cause energy inefficiency in terms of the number of poor utilization interfaces. To tackle this energy inefficiency, traffic off-balancing algorithm for traffic adaptive interface sleep/awake is investigated. As a reference model, 40G/100G Ethernet is investigated. We report that suggested algorithm can achieve energy efficiency while satisfying traffic transmission requirement.
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paper_title: Millimeter Wave Mobile Communications for 5G Cellular: It Will Work!

paper_content:

The global bandwidth shortage facing wireless carriers has motivated the exploration of the underutilized millimeter wave (mm-wave) frequency spectrum for future broadband cellular communication networks. There is, however, little knowledge about cellular mm-wave propagation in densely populated indoor and outdoor environments. Obtaining this information is vital for the design and operation of future fifth generation cellular networks that use the mm-wave spectrum. In this paper, we present the motivation for new mm-wave cellular systems, methodology, and hardware for measurements and offer a variety of measurement results that show 28 and 38 GHz frequencies can be used when employing steerable directional antennas at base stations and mobile devices.
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paper_title: Energy-aware resource allocation for device-to-device underlay communication

paper_content:

Device-to-device (D2D) communication as an underlay to cellular networks brings significant benefits to users' throughput and battery lifetime. The allocation of power and channel resources to D2D communication needs elaborate coordination, as D2D user equipments (UEs) cause interference to other UEs. In this paper, we propose a novel resource allocation scheme to improve the performance of D2D communication. Battery lifetime is explicitly considered as our optimization goal. We first formulate the allocation problem as a non-cooperative resource allocation game in which D2D UEs are viewed as players competing for channel resources. Then, we add pricing to the game in order to improve the efficacy, and propose an efficient auction algorithm. We also perform simulations to prove efficacy of the proposed algorithm.
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paper_title: Energy Efficient Visible Light Communications Relying on Amorphous Cells

paper_content:

In this paper, we design an energy efficient indoor visible light communications (VLC) system from a radically new perspective based on an amorphous user-to-network association structure. Explicitly, this intriguing problem is approached from three inter-linked perspectives, considering the cell formation, link-level transmission and system-level optimisation, critically appraising the related optical constraints. To elaborate, apart from proposing hitherto unexplored amorphous cells (A-Cells), we employ a powerful amalgam of asymmetrically clipped optical orthogonal frequency division multiplexing (ACO-OFDM) and transmitter pre-coding aided multi-input single-output (MISO) transmission. As far as the overall system-level optimisation is concerned, we propose a low-complexity solution dispensing with the classic Dinkelbach’s algorithmic structure. Our numerical study compares a range of different cell formation strategies and investigates diverse design aspects of the proposed A-Cells. Specifically, our results show that the A-Cells proposed are capable of achieving a much higher energy efficiency per user compared to that of the conventional cell formation for a range of practical field of views (FoVs) angles.
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paper_title: Visible light communications for 5G wireless networking systems: from fixed to mobile communications

paper_content:

Visible light communication, considered as a potential access option for 5G wireless communications, is gaining extensive attention. VLC has strengths in energy efficiency and ultra wide bandwidth, but also has weakness in transmission range and obstacles in transmission paths. This article aims to provide a conclusive investigation of the latest progress in research on VLC, which can be used as part of 5G wireless communication systems. This work highlights the strengths and weaknesses of VLC in comparison with RF-based communications, especially in spectrum, spatial reuse, security and energy efficiency. The article also investigates various lighting sources proposed for VLC systems. It summarizes the literature work on VLC networking into two categories: fixed and mobile VLC communications.
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paper_title: Energy Efficiency of Downlink Networks with Caching at Base Stations

paper_content:

Caching popular contents at base stations (BSs) can reduce the backhaul cost and improve the network throughput. Yet whether locally caching at the BSs can improve the energy efficiency (EE), a major goal for fifth generation cellular networks, remains unclear. Due to the entangled impact of various factors on EE such as interference level, backhaul capacity, BS density, power consumption parameters, BS sleeping, content popularity, and cache capacity, another important question is what are the key factors that contribute more to the EE gain from caching. In this paper, we attempt to explore the potential of EE of the cache-enabled wireless access networks and identify the key factors. By deriving closed-form expression of the approximated EE, we provide the condition when the EE can benefit from caching, find the optimal cache capacity that maximizes the network EE, and analyze the maximal EE gain brought by caching. We show that caching at the BSs can improve the network EE when power efficient cache hardware is used. When local caching has EE gain over not caching, caching more contents at the BSs may not provide higher EE. Numerical and simulation results show that the caching EE gain is large when the backhaul capacity is stringent, interference level is low, content popularity is skewed, and when caching at pico BSs instead of macro BSs.
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paper_title: Five Disruptive Technology Directions for 5G

paper_content:

New research directions will lead to fundamental changes in the design of future 5th generation (5G) cellular networks. This paper describes five technologies that could lead to both architectural and component disruptive design changes: device-centric architectures, millimeter Wave, Massive-MIMO, smarter devices, and native support to machine-2-machine. The key ideas for each technology are described, along with their potential impact on 5G and the research challenges that remain.
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paper_title: Assessing System-Level Energy Efficiency of mmWave-Based Wearable Networks

paper_content:

The emerging fifth-generation (5G) wireless technology will need to harness the massively unused millimeter-wave (mmWave) spectrum to meet the projected acceleration in mobile traffic demand. Today, the available range of mmWave-based solutions is already represented by IEEE 802.11ad (WiGig), IEEE 802.15.3c, WirelessHD, and ECMA-387 standards, with more to come in the following years. As the key performance-related aspects of these enabling technologies are rapidly taking shape, the primary research challenge shifts to characterizing network energy efficiency, among other system-level parameters. This is particularly important in scenarios that are not handled by current 4G communication networks, including congested public places, homes, and offices. In these dense deployments, wireless wearable devices are increasingly proliferating to assist in diverse user needs. However, mmWave operation in crowded environments, and especially for multiple neighboring personal networks, is not nearly well-understood. Bridging this gap, we conduct a full-fledged energy efficiency assessment of mmWave-based “high-end” wearables that employ advanced antenna beamforming techniques. Our rigorous analytical results shed light on the underlying scaling laws for the interacting mmWave-based networks based on IEEE 802.11ad and quantify the impact of beamforming quality on system energy efficiency under various conditions. Furthermore, we look at the system optimization potential subject to realistic hardware capabilities.
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paper_title: Energy Efficient Resource Allocation for Mixed RF/VLC Heterogeneous Wireless Networks

paper_content:

Developing energy efficient wireless communication networks has become crucial due to the associated environmental and financial benefits. Visible light communication (VLC) has emerged as a promising candidate for achieving energy efficient wireless communications. Integrating VLC with radio frequency (RF)-based wireless networks has improved the achievable data rates of mobile users. In this paper, we investigate the energy efficiency benefits of integrating VLC with RF-based networks in a heterogeneous wireless environment. We formulate and solve the problem of power and bandwidth allocation for energy efficiency maximization of a heterogeneous network composed of a VLC system and an RF communication system. Then, we investigate the impact of the system parameters on the energy efficiency of the mixed RF/VLC heterogeneous network. Numerical results are conducted to corroborate the superiority in performance of the proposed hybrid system. The impact of hybrid system parameters on the overall energy efficiency is also quantified.
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paper_title: Fundamental Tradeoffs on Energy-Aware D2D Communication Underlaying Cellular Networks: A Dynamic Graph Approach

paper_content:

With the ever-increasing energy consumption in transmissions of explosive growing mobile data, energy-efficient solutions are needed to be integrated into the future mobile networks. The upcoming 5G networks support device-to-device (D2D) communication underlaying the cellular networks, which enables proximity cellular users to communicate directly with high data rate and low transmit power. In this paper, targeting the energy-aware D2D communications underlaying cellular system, we investigate the fundamental problems of what is the potential gains of D2D communications for energy saving, which are the fundamental reasons to decrease the energy consumption, and how about the tradeoffs between energy consumption and other network factors of available bandwidth, buffer size and service delay in large scale D2D communication networks. To answer the above challenging problems, we utilize a dynamic graph approach to model the system with human mobility for a realistic D2D communication scenario. Specifically, by formulating a mixed integer linear programming problem that minimizes the energy consumption for data transmission from the cellular base stations to the receivers through any possible ways of transmissions, we obtain the theoretical performance lower bound of system energy consumption, which shows that cellular D2D communications decrease the energy consumption about 65% averagely under the realistic scenario. Furthermore, the obtained fundamental tradeoffs reveal that energy consumption for large bandwidth can be kept at a low level with increase of the buffer size and service delay.
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paper_title: Living on the edge: The role of proactive caching in 5G wireless networks

paper_content:

This article explores one of the key enablers of beyond 4G wireless networks leveraging small cell network deployments, proactive caching. Endowed with predictive capabilities and harnessing recent developments in storage, context awareness, and social networks, peak traffic demands can be substantially reduced by proactively serving predictable user demands via caching at base stations and users' devices. In order to show the effectiveness of proactive caching, we examine two case studies that exploit the spatial and social structure of the network, where proactive caching plays a crucial role. First, in order to alleviate backhaul congestion, we propose a mechanism whereby files are proactively cached during off-peak periods based on file popularity and correlations among user and file patterns. Second, leveraging social networks and D2D communications, we propose a procedure that exploits the social structure of the network by predicting the set of influential users to (proactively) cache strategic contents and disseminate them to their social ties via D2D communications. Exploiting this proactive caching paradigm, numerical results show that important gains can be obtained for each case study, with backhaul savings and a higher ratio of satisfied users of up to 22 and 26 percent, respectively. Higher gains can be further obtained by increasing the storage capability at the network edge.
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paper_title: Optimal Adaptive Random Multiaccess in Energy Harvesting Wireless Sensor Networks

paper_content:

Wireless sensors can integrate rechargeable batteries and energy-harvesting (EH) devices to enable long-term, autonomous operation, thus requiring intelligent energy management to limit the adverse impact of energy outages. This work considers a network of EH wireless sensors, which report packets with a random utility value to a fusion center (FC) over a shared wireless channel. Decentralized access schemes are designed, where each node performs a local decision to transmit/discard a packet, based on an estimate of the packet's utility, its own energy level, and the scenario state of the EH process, with the objective to maximize the average long-term aggregate utility of the packets received at the FC. Due to the non-convex structure of the problem, an approximate optimization is developed by resorting to a mathematical artifice based on a game theoretic formulation of the multiaccess scheme, where the nodes do not behave strategically, but rather attempt to maximize a common network utility with respect to their own policy. The symmetric Nash equilibrium (SNE) is characterized, where all nodes employ the same policy; its uniqueness is proved, and it is shown to be a local maximum of the original problem. An algorithm to compute the SNE is presented, and a heuristic scheme is proposed, which is optimal for large battery capacity. It is shown numerically that the SNE typically achieves near-optimal performance, within 3% of the optimal policy, at a fraction of the complexity, and two operational regimes of EH-networks are identified and analyzed: an energy-limited scenario , where energy is scarce and the channel is under-utilized, and a network-limited scenario , where energy is abundant and the shared wireless channel represents the bottleneck of the system.
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paper_title: Modeling and Analysis of Energy Consumption for RF Transceivers in Wireless Cellular Systems

paper_content:

In this paper, a comprehensive model has been provided to study the energy consumption of wireless cellular devices, by analyzing the relationship between the modulation order and energy consumption of the power amplifier (PA) and other circuits in radio frequency transceivers. Two types of energy consumption for PAs are studied in detail: transmitted energy, which is provided to the antenna to transmit data, and energy dissipated as a heat. First, the transmitted energy is studied along with different modulation orders for different distances between the transmitter and receiver. Next, the dissipated energy with all corresponding parameters such as peak to average ratio (PAR) and the drain efficiency of the PA is discussed. Other circuits are examined to show that the energy of these circuits--unlike other models in the literature--change with modulation order. The results reinforce the idea that increasing the modulation order leads to higher energy consumption in the RF transceiver for large distance. The results also show that the energy dissipated due to PAR and drain efficiency is larger than the transmitted energy.
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paper_title: Optimum Transmission Policies for Battery Limited Energy Harvesting Nodes

paper_content:

Wireless networks with energy harvesting battery equipped nodes are quickly emerging as a viable option for future wireless networks with extended lifetime. Equally important to their counterpart in the design of energy harvesting radios are the design principles that this new networking paradigm calls for. In particular, unlike wireless networks considered to date, the energy replenishment process and the storage constraints of the rechargeable batteries need to be taken into account in designing efficient transmission strategies. In this work, such transmission policies for rechargeable nodes are considered, and optimum solutions for two related problems are identified. Specifically, the transmission policy that maximizes the short term throughput, i.e., the amount of data transmitted in a finite time horizon is found. In addition, the relation of this optimization problem to another, namely, the minimization of the transmission completion time for a given amount of data is demonstrated, which leads to the solution of the latter as well. The optimum transmission policies are identified under the constraints on energy causality, i.e., energy replenishment process, as well as the energy storage, i.e., battery capacity. For battery replenishment, a model with discrete packets of energy arrivals is considered. The necessary conditions that the throughput-optimal allocation satisfies are derived, and then the algorithm that finds the optimal transmission policy with respect to the short-term throughput and the minimum transmission completion time is given. Numerical results are presented to confirm the analytical findings.
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paper_title: Energy-Efficient Hybrid Analog and Digital Precoding for MmWave MIMO Systems With Large Antenna Arrays

paper_content:

Millimeter wave (mmWave) MIMO will likely use hybrid analog and digital precoding, which uses a small number of RF chains to reduce the energy consumption associated with mixed signal components like analog-to-digital components not to mention baseband processing complexity. However, most hybrid precoding techniques consider a fully connected architecture requiring a large number of phase shifters, which is also energy-intensive. In this paper, we focus on the more energy-efficient hybrid precoding with subconnected architecture, and propose a successive interference cancelation (SIC)-based hybrid precoding with near-optimal performance and low complexity. Inspired by the idea of SIC for multiuser signal detection, we first propose to decompose the total achievable rate optimization problem with nonconvex constraints into a series of simple subrate optimization problems, each of which only considers one subantenna array. Then, we prove that maximizing the achievable subrate of each subantenna array is equivalent to simply seeking a precoding vector sufficiently close (in terms of Euclidean distance) to the unconstrained optimal solution. Finally, we propose a low-complexity algorithm to realize SIC-based hybrid precoding, which can avoid the need for the singular value decomposition (SVD) and matrix inversion. Complexity evaluation shows that the complexity of SIC-based hybrid precoding is only about 10% as complex as that of the recently proposed spatially sparse precoding in typical mmWave MIMO systems. Simulation results verify that SIC-based hybrid precoding is near-optimal and enjoys higher energy efficiency than the spatially sparse precoding and the fully digital precoding.
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paper_title: Wireless Networks With RF Energy Harvesting: A Contemporary Survey

paper_content:

Radio frequency (RF) energy transfer and harvesting techniques have recently become alternative methods to power the next generation wireless networks. As this emerging technology enables proactive energy replenishment of wireless devices, it is advantageous in supporting applications with quality of service (QoS) requirement. In this paper, we present an extensive literature review on the research progresses in wireless networks with RF energy harvesting capability, referred to as RF energy harvesting networks (RF-EHNs). First, we present an overview of the RF-EHNs including system architecture, RF energy harvesting techniques and existing applications. Then, we present the background in circuit design as well as the state-of-the-art circuitry implementations, and review the communication protocols specially designed for RF-EHNs. We also explore various key design issues in the development of RF-EHNs according to the network types, i.e., single-hop network, multi-antenna network, relay network and cognitive radio network. Finally, we envision some open research directions.
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paper_title: Traffic-Aware Cloud RAN: A Key for Green 5G Networks

paper_content:

Next generation 5G wireless networks envision innovative radio technologies for ultra dense deployment with improved coverage and higher data rates. However, the deployment of ultra dense 5G networks, with relatively smaller cells, raises significant challenges in network energy consumption. Emerging green cloud radio access networks (C-RANs) are providing assurance of energy efficient cellular operations for reduction of both greenhouse emissions and operators’ energy bill. Cellular traffic dynamics play a significant role in efficient network energy management. In this paper, we first identify the complexity of the optimal traffic awareness in 5G C-RAN and design a framework for traffic-aware energy optimization. The virtual base station cluster (VBSC) of C-RAN exploits an information theoretic approach to model and analyze the uncertainty of cellular traffic, captured by remote radio heads (RRH). Subsequently, using an online, stochastic game theoretic algorithm, the VBS instances optimize and learn the cellular traffic patterns. Efficient learning makes the C-RAN aware of the near-future traffic. Traffic awareness helps in selective switching of a subset of RRHs, thus reducing the overall energy consumption. Our VBS prototype implementation, testbed experiments, and simulation results, performed with actual cellular traffic traces, demonstrate that our framework results in almost 25% daily energy savings and 35% increased energy efficiency with a negligible overhead.
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paper_title: Mixed-ADC Massive MIMO

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Motivated by the demand for energy-efficient communication solutions in the next generation cellular network, a mixed-ADC architecture for massive multiple-input-multiple-output (MIMO) systems is proposed, which differs from previous works in that herein one-bit analog-to-digital converters (ADCs) partially replace the conventionally assumed high-resolution ADCs. The information-theoretic tool of generalized mutual information (GMI) is exploited to analyze the achievable data rates of the proposed system architecture and an array of analytical results of engineering interest are obtained. For fixed single-input-multiple-output (SIMO) channels, a closed-form expression of the GMI is derived, based on which the linear combiner is optimized. The analysis is then extended to ergodic fading channels, for which tight lower and upper bounds of the GMI are obtained. Impacts of dithering and imperfect channel state information (CSI) are also investigated, and it is shown that dithering can remarkably improve the system performance while imperfect CSI only introduces a marginal rate loss. Finally, the analytical framework is applied to the multiuser access scenario. Numerical results demonstrate that the mixed-ADC architecture with a relatively small number of high-resolution ADCs is able to achieve a large fraction of the channel capacity of conventional architecture, while reduce the energy consumption considerably even compared with antenna selection, for both single-user and multiuser scenarios.
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paper_title: MIMO Beamforming Designs With Partial CSI Under Energy Harvesting Constraints

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In this letter, we investigate multiple-input multiple-output (MIMO) communications under energy harvesting (EH) constraints. In our considered EH system, there is one information transmitting (ITx) node, one traditional information receiving (IRx) node and multiple EH nodes. EH nodes can transform the received electromagnetic waves into energy to enlarge the network operation life. When the ITx node sends signals to the destination, it should also optimize the beamforming/precoder matrix to charge the EH nodes efficiently simultaneously. Additionally, the charged energy should be larger than a predefined threshold. Under the EH constraints, in our work both minimum mean-square-error (MMSE) and mutual information are taken as the performance metrics for the beamforming designs at the ITx node. In order to make the proposed algorithms suitable for practical implementation and have affordable overhead, our work focuses on the beamforming designs with partial CSI and this is the distinct contribution of our work. Finally, numerical results are given to show the performance advantages of the proposed algorithms.
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paper_title: Optimal Packet Scheduling in an Energy Harvesting Communication System

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We consider the optimal packet scheduling problem in a single-user energy harvesting wireless communication system. In this system, both the data packets and the harvested energy are modeled to arrive at the source node randomly. Our goal is to adaptively change the transmission rate according to the traffic load and available energy, such that the time by which all packets are delivered is minimized. Under a deterministic system setting, we assume that the energy harvesting times and harvested energy amounts are known before the transmission starts. For the data traffic arrivals, we consider two different scenarios. In the first scenario, we assume that all bits have arrived and are ready at the transmitter before the transmission starts. In the second scenario, we consider the case where packets arrive during the transmissions, with known arrival times and sizes. We develop optimal off-line scheduling policies which minimize the time by which all packets are delivered to the destination, under causality constraints on both data and energy arrivals.
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paper_title: Large scale antenna system with hybrid digital and analog beamforming structure

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Large scale antenna systems (LSAS) are expected to significantly enhance the energy efficiency (EE) and spectrum efficiency (SE) of wireless communication systems. However, there are many open issues regarding the implementation of digital beamforming (BF) structures: calibration, complexity, and cost. In a practical LSAS deployment, hybrid digital and analog BF structures with active antennas can be an alternative choice. In this paper, an N (the number of transceivers) by M (the number of active antennas per transceiver) hybrid BF structure is investigated, where the analog BF is performed per transceiver and digital BF is performed across N transceivers. Analysis of the N by M BF structure includes: the optimal analog and digital BF design, EE-SE relationship at the green point (i.e. the point with highest EE) in EE-SE curve, impact of N on EE performance at a given SE value, and impact of N on the green point EE. Numerical simulations are provided to support the analysis.
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paper_title: Cloud technologies for flexible 5G radio access networks

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The evolution toward 5G mobile networks will be characterized by an increasing number of wireless devices, increasing device and service complexity, and the requirement to access mobile services ubiquitously. Two key enablers will allow the realization of the vision of 5G: very dense deployments and centralized processing. This article discusses the challenges and requirements in the design of 5G mobile networks based on these two key enablers. It discusses how cloud technologies and flexible functionality assignment in radio access networks enable network densification and centralized operation of the radio access network over heterogeneous backhaul networks. The article describes the fundamental concepts, shows how to evolve the 3GPP LTE a
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paper_title: Relaying Protocols for Wireless Energy Harvesting and Information Processing

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An emerging solution for prolonging the lifetime of energy constrained relay nodes in wireless networks is to avail the ambient radio-frequency (RF) signal and to simultaneously harvest energy and process information. In this paper, an amplify-and-forward (AF) relaying network is considered, where an energy constrained relay node harvests energy from the received RF signal and uses that harvested energy to forward the source information to the destination. Based on the time switching and power splitting receiver architectures, two relaying protocols, namely, i) time switching-based relaying (TSR) protocol and ii) power splitting-based relaying (PSR) protocol are proposed to enable energy harvesting and information processing at the relay. In order to determine the throughput, analytical expressions for the outage probability and the ergodic capacity are derived for delay-limited and delay-tolerant transmission modes, respectively. The numerical analysis provides practical insights into the effect of various system parameters, such as energy harvesting time, power splitting ratio, source transmission rate, source to relay distance, noise power, and energy harvesting efficiency, on the performance of wireless energy harvesting and information processing using AF relay nodes. In particular, the TSR protocol outperforms the PSR protocol in terms of throughput at relatively low signal-to-noise-ratios and high transmission rate.
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paper_title: A Survey on Power-Amplifier-Centric Techniques for Spectrum- and Energy-Efficient Wireless Communications

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In this paper, we provide a survey on techniques to improve the spectrum and energy efficiency of wireless communication systems. Recognizing the fact that power amplifier (PA) is one of the most critical components in wireless communication systems and consumes a significant fraction of the total energy, we take a bottom-up approach to focus on PA-centric designs. In the first part of the survey, we introduce the fundamental properties of the PA, such as linearity and efficiency . Next, we quantify the detrimental effects of the signal non-linearity and power inefficiency of the PA on the spectrum efficiency (SE) and energy efficiency (EE) of wireless communications. In the last part, we survey known mitigation techniques from three perspectives: PA design , signal design and network design . We believe that this broad understanding will help motivate holistic design approaches to mitigate the non-ideal effects in real-life PA devices, and accelerate cross-domain research to further enhance the available techniques.
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paper_title: Energy-Efficient Resource Allocation in OFDMA Systems with Hybrid Energy Harvesting Base Station

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We study resource allocation algorithm design for energy-efficient communication in an orthogonal frequency division multiple access (OFDMA) downlink network with hybrid energy harvesting base station (BS). Specifically, an energy harvester and a constant energy source driven by a non-renewable resource are used for supplying the energy required for system operation. We first consider a deterministic offline system setting. In particular, assuming availability of non-causal knowledge about energy arrivals and channel gains, an offline resource allocation problem is formulated as a non-convex optimization problem over a finite horizon taking into account the circuit energy consumption, a finite energy storage capacity, and a minimum required data rate. We transform this non-convex optimization problem into a convex optimization problem by applying time-sharing and exploiting the properties of non-linear fractional programming which results in an efficient asymptotically optimal offline iterative resource allocation algorithm for a sufficiently large number of subcarriers. In each iteration, the transformed problem is solved by using Lagrange dual decomposition. The obtained resource allocation policy maximizes the weighted energy efficiency of data transmission (weighted bit/Joule delivered to the receiver). Subsequently, we focus on online algorithm design. A conventional stochastic dynamic programming approach is employed to obtain the optimal online resource allocation algorithm which entails a prohibitively high complexity. To strike a balance between system performance and computational complexity, we propose a low complexity suboptimal online iterative algorithm which is motivated by the offline algorithm. Simulation results illustrate that the proposed suboptimal online iterative resource allocation algorithm does not only converge in a small number of iterations, but also achieves a close-to-optimal system energy efficiency by utilizing only causal channel state and energy arrival information.
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paper_title: Wireless-Powered Cooperative Communications: Power-Splitting Relaying with Energy Accumulation

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A harvest-use-store power splitting (PS) relaying strategy with distributed beamforming is proposed for wireless-powered multi-relay cooperative networks in this paper. Different from the conventional battery-free PS relaying strategy, harvested energy is prioritized to power information relaying while the remainder is accumulated and stored for future usage with the help of a battery in the proposed strategy, which supports an efficient utilization of harvested energy. However, PS affects throughput at subsequent time slots due to the battery operations including the charging and discharging. To this end, PS and battery operations are coupled with distributed beamforming. A throughput optimization problem to incorporate these coupled operations is formulated though it is intractable. To address the intractability of the optimization, a layered optimization method is proposed to achieve the optimal joint PS and battery operation design with non-causal channel state information (CSI), in which the PS and the battery operation can be analyzed in a decomposed manner. Then, a general case with causal CSI is considered, where the proposed layered optimization method is extended by utilizing the statistical properties of CSI. To reach a better tradeoff between performance and complexity, a greedy method that requires no information about subsequent time slots is proposed. Simulation results reveal the upper and lower bound on performance of the proposed strategy, which are reached by the layered optimization method with non-causal CSI and the greedy method, respectively. Moreover, the proposed strategy outperforms the conventional PS-based relaying without energy accumulation and time switching-based relaying strategy.
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paper_title: Energy cooperation in cellular networks with renewable powered base stations

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In this paper, we propose a model for energy cooperation between cellular base stations (BSs) with individual renewable energy sources, limited energy storages and connected by resistive power lines for energy sharing. When the renewable energy profile and energy demand profile at all BSs are deterministic or known ahead of time, we show that the optimal energy cooperation policy for the BSs can be found by solving a linear program. We show the benefits of energy cooperation in this regime. When the renewable energy and demand profiles are stochastic and only causally known at the BSs, we propose an online energy cooperation algorithm and show the optimality properties of this algorithm under certain conditions. Furthermore, the energy-saving performances of the developed offline and online algorithms are compared by simulations, and the effect of the availability of energy state information (ESI) on the performance gains of the BSs' energy cooperation is investigated.
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paper_title: Wireless Information and Power Transfer: Energy Efficiency Optimization in OFDMA Systems

paper_content:

This paper considers orthogonal frequency division multiple access (OFDMA) systems with simultaneous wireless information and power transfer. We study the resource allocation algorithm design for maximization of the energy efficiency of data transmission (bits/Joule delivered to the receivers). In particular, we focus on power splitting hybrid receivers which are able to split the received signals into two power streams for concurrent information decoding and energy harvesting. Two scenarios are investigated considering different power splitting abilities of the receivers. In the first scenario, we assume receivers which can split the received power into a continuous set of power streams with arbitrary power splitting ratios. In the second scenario, we examine receivers which can split the received power only into a discrete set of power streams with fixed power splitting ratios. For both scenarios, we formulate the corresponding algorithm design as a non-convex optimization problem which takes into account the circuit power consumption, the minimum data rate requirements of delay constrained services, the minimum required system data rate, and the minimum amount of power that has to be delivered to the receivers. By exploiting fractional programming and dual decomposition, suboptimal iterative resource allocation algorithms are developed to solve the non-convex problems. Simulation results illustrate that the proposed iterative resource allocation algorithms approach the optimal solution within a small number of iterations and unveil the trade-off between energy efficiency, system capacity, and wireless power transfer: (1) wireless power transfer enhances the system energy efficiency by harvesting energy in the radio frequency, especially in the interference limited regime; (2) the presence of multiple receivers is beneficial for the system capacity, but not necessarily for the system energy efficiency.
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paper_title: Designing intelligent energy harvesting communication systems

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From being a scientific curiosity only a few years ago, energy harvesting (EH) is well on its way to becoming a game-changing technology in the field of autonomous wireless networked systems. The promise of long-term, uninterrupted and self-sustainable operation in a diverse array of applications has captured the interest of academia and industry alike. Yet the road to the ultimate network of perpetual communicating devices is plagued with potholes: ambient energy is intermittent and scarce, energy storage capacity is limited, and devices are constrained in size and complexity. In dealing with these challenges, this article will cover recent developments in the design of intelligent energy management policies for EH wireless devices and discuss pressing research questions in this rapidly growing field.
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paper_title: Sum-rate optimal power policies for energy harvesting transmitters in an interference channel

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This paper considers a two-user Gaussian interference channel with energy harvesting transmitters. Different than conventional battery powered wireless nodes, energy harvesting transmitters have to adapt transmission to availability of energy at a particular instant. In this setting, the optimal power allocation problem to maximize the sum throughput with a given deadline is formulated. The convergence of the proposed iterative coordinate descent method for the problem is proved and the short-term throughput maximizing offline power allocation policy is found. Examples for interference regions with known sum capacities are given with directional waterfilling interpretations. Next, stochastic data arrivals are addressed. Finally, online and/or distributed near-optimal policies are proposed. Performance of the proposed algorithms are demonstrated through simulations.
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paper_title: Power Allocation Strategies in Energy Harvesting Wireless Cooperative Networks

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In this paper, a wireless cooperative network is considered, in which multiple source-destination pairs communicate with each other via an energy harvesting relay. The focus of this paper is on the relay's strategies to distribute the harvested energy among the multiple users and their impact on the system performance. Specifically, a non-cooperative strategy that uses the energy harvested from the i-th source as the relay transmission power to the i-th destination is considered first, and asymptotic results show that its outage performance decays as log SNR/SNR. A faster decay rate, 1/SNR, can be achieved by two centralized strategies proposed next, of which a water filling based one can achieve optimal performance with respect to several criteria, at the price of high complexity. An auction based power allocation scheme is also proposed to achieve a better tradeoff between system performance and complexity. Simulation results are provided to confirm the accuracy of the developed analytical results.
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paper_title: RF Energy Harvesting and Transport for Wireless Sensor Network Applications: Principles and Requirements

paper_content:

This paper presents an overview of principles and requirements for powering wireless sensors by radio-frequency (RF) energy harvesting or transport. The feasibility of harvesting is discussed, leading to the conclusion that RF energy transport is preferred for powering small sized sensors. These sensors are foreseen in future Smart Buildings. Transmitting in the ISM frequency bands, respecting the transmit power limits ensures that the International Commission on Non-Ionizing Radiation Protection (ICNIRP) exposure limits are not exceeded. With the transmit side limitations being explored, the propagation channel is next discussed, leading to the observation that a better than free-space attenuation may be achieved in indoors line-of-sight environments. Then, the components of the rectifying antenna (rectenna) are being discussed: rectifier, dc-dc boost converter, and antenna. The power efficiencies of all these rectenna subcomponents are being analyzed and finally some examples are shown. To make RF energy transport a feasible powering technology for low-power sensors, a number of precautions need to be taken. The propagation channel characteristics need to be taken into account by creating an appropriate transmit antenna radiation pattern. All subcomponents of the rectenna need to be impedance matched, and the power transfer efficiencies of the rectifier and the boost converter need to be optimized.
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paper_title: Optimal Energy Allocation for Wireless Communications With Energy Harvesting Constraints

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We consider the use of energy harvesters, in place of conventional batteries with fixed energy storage, for point-to-point wireless communications. In addition to the challenge of transmitting in a channel with time selective fading, energy harvesters provide a perpetual but unreliable energy source. In this paper, we consider the problem of energy allocation over a finite horizon, taking into account channel conditions and energy sources that are time varying, so as to maximize the throughput. Two types of side information (SI) on the channel conditions and harvested energy are assumed to be available: causal SI (of the past and present slots) or full SI (of the past, present and future slots). We obtain structural results for the optimal energy allocation, via the use of dynamic programming and convex optimization techniques. In particular, if unlimited energy can be stored in the battery with harvested energy and the full SI is available, we prove the optimality of a water-filling energy allocation solution where the so-called water levels follow a staircase function.
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paper_title: Energy Efficient Beamforming in MISO Heterogeneous Cellular Networks With Wireless Information and Power Transfer

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The advent of simultaneous wireless information and power transfer (SWIPT) offers a promising approach to providing cost-effective and perpetual power supplies for energy-constrained mobile devices in heterogeneous cellular networks (HCNs). As energy efficiency (EE) has been envisioned as a key performance metric in 5G wireless networks, we consider a multiple-input single-output (MISO) femtocell cochannel overlaid with a Macrocell to exploit the advantages of SWIPT while promoting the EE. The femto base station sends information to information decoding (ID) femto users (FUs) and transfers energy to energy harvesting (EH) FUs simultaneously, and also suppresses its interference to Macro users. We maximize the information transmission efficiency (ITE) of ID FUs and energy harvesting efficiency (EHE) of EH FUs, respectively, with the QoS of all users, and investigate their relationship. We formulate these problems as fractional programming, which are nontrivial to solve due to the nonconvexity of ITE and EHE. To tackle these problems, we devise two beamformers namely zero-forcing (ZF) and mixed beamforming (MBF), and then propose an efficient algorithm to obtain the optimal power under both beamformers. Simulation results demonstrate that MBF provides better ITE and EHE than ZF, and there exists a tradeoff between ITE and EHE in general.
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paper_title: Simultaneous Information and Power Transfer for Broadband Wireless Systems

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Far-field microwave power transfer (MPT) will free wireless sensors and other mobile devices from the constraints imposed by finite battery capacities. Integrating MPT with wireless communications to support simultaneous wireless information and power transfer (SWIPT) allows the same spectrum to be used for dual purposes without compromising the quality of service. A novel approach is presented in this paper for realizing SWIPT in a broadband system where orthogonal frequency division multiplexing and transmit beamforming are deployed to create a set of parallel sub-channels for SWIPT, which simplifies resource allocation. Based on a proposed reconfigurable mobile architecture, different system configurations are considered by combining single-user/multi-user systems, downlink/uplink information transfer, and variable/fixed coding rates. Optimizing the power control for these configurations results in a new class of multi-user power-control problems featuring the circuit-power constraints, specifying that the transferred power must be sufficiently large to support the operation of the receiver circuitry. Solving these problems gives a set of power-control algorithms that exploit channel diversity in frequency for simultaneously enhancing the throughput and the MPT efficiency. For the system configurations with variable coding rates, the algorithms are variants of water-filling that account for the circuit-power constraints. The optimal algorithms for those configurations with fixed coding rates are shown to sequentially allocate mobiles their required power for decoding in ascending order until the entire budgeted power is spent. The required power for a mobile is derived as simple functions of the minimum signal-to-noise ratio for correct decoding, the circuit power and sub-channel gains.
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paper_title: Energy Efficiency of Downlink Transmission Strategies for Cloud Radio Access Networks

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This paper studies the energy efficiency of the cloud radio access network (C-RAN), specifically focusing on two fundamental and different downlink transmission strategies, namely the data-sharing strategy and the compression strategy. In the data-sharing strategy, the backhaul links connecting the central processor (CP) and the base-stations (BSs) are used to carry user messages—each user’s messages are sent to multiple BSs; the BSs locally form the beamforming vectors then cooperatively transmit the messages to the user. In the compression strategy, the user messages are precoded centrally at the CP, which forwards a compressed version of the analog beamformed signals to the BSs for cooperative transmission. This paper compares the energy efficiencies of the two strategies by formulating an optimization problem of minimizing the total network power consumption subject to user target rate constraints, where the total network power includes the BS transmission power, BS activation power, and load-dependent backhaul power. To tackle the discrete and nonconvex nature of the optimization problems, we utilize the techniques of reweighted $\ell_1$ minimization and successive convex approximation to devise provably convergent algorithms. Our main finding is that both the optimized data-sharing and compression strategies in C-RAN achieve much higher energy efficiency as compared to the nonoptimized coordinated multipoint transmission, but their comparative effectiveness in energy saving depends on the user target rate. At low user target rate, data-sharing consumes less total power than compression; however, as the user target rate increases, the backhaul power consumption for data-sharing increases significantly leading to better energy efficiency of compression at the high user rate regime.
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paper_title: Spatially Sparse Precoding in Millimeter Wave MIMO Systems

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Millimeter wave (mmWave) signals experience orders-of-magnitude more pathloss than the microwave signals currently used in most wireless applications. MmWave systems must therefore leverage large antenna arrays, made possible by the decrease in wavelength, to combat pathloss with beamforming gain. Beamforming with multiple data streams, known as precoding, can be used to further improve mmWave spectral efficiency. Both beamforming and precoding are done digitally at baseband in traditional multi-antenna systems. The high cost and power consumption of mixed-signal devices in mmWave systems, however, make analog processing in the RF domain more attractive. This hardware limitation restricts the feasible set of precoders and combiners that can be applied by practical mmWave transceivers. In this paper, we consider transmit precoding and receiver combining in mmWave systems with large antenna arrays. We exploit the spatial structure of mmWave channels to formulate the precoding/combining problem as a sparse reconstruction problem. Using the principle of basis pursuit, we develop algorithms that accurately approximate optimal unconstrained precoders and combiners such that they can be implemented in low-cost RF hardware. We present numerical results on the performance of the proposed algorithms and show that they allow mmWave systems to approach their unconstrained performance limits, even when transceiver hardware constraints are considered.
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paper_title: Broadcasting with an Energy Harvesting Rechargeable Transmitter

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In this paper, we investigate the transmission completion time minimization problem in a two-user additive white Gaussian noise (AWGN) broadcast channel, where the transmitter is able to harvest energy from the nature, using a rechargeable battery. The harvested energy is modeled to arrive at the transmitter randomly during the course of transmissions. The transmitter has a fixed number of packets to be delivered to each receiver. Our goal is to minimize the time by which all of the packets for both users are delivered to their respective destinations. To this end, we optimize the transmit powers and transmission rates intended for both users. We first analyze the structural properties of the optimal transmission policy. We prove that the optimal total transmit power has the same structure as the optimal single-user transmit power. We also prove that there exists a cut-off power level for the stronger user. If the optimal total transmit power is lower than this cut-off level, all transmit power is allocated to the stronger user, and when the optimal total transmit power is larger than this cut-off level, all transmit power above this level is allocated to the weaker user. Based on these structural properties of the optimal policy, we propose an algorithm that yields the globally optimal off-line scheduling policy. Our algorithm is based on the idea of reducing the two-user broadcast channel problem into a single-user problem as much as possible.
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paper_title: Transmission with Energy Harvesting Nodes in Fading Wireless Channels: Optimal Policies

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Wireless systems comprised of rechargeable nodes have a significantly prolonged lifetime and are sustainable. A distinct characteristic of these systems is the fact that the nodes can harvest energy throughout the duration in which communication takes place. As such, transmission policies of the nodes need to adapt to these harvested energy arrivals. In this paper, we consider optimization of point-to-point data transmission with an energy harvesting transmitter which has a limited battery capacity, communicating in a wireless fading channel. We consider two objectives: maximizing the throughput by a deadline, and minimizing the transmission completion time of the communication session. We optimize these objectives by controlling the time sequence of transmit powers subject to energy storage capacity and causality constraints. We, first, study optimal offline policies. We introduce a directional water-filling algorithm which provides a simple and concise interpretation of the necessary optimality conditions. We show the optimality of an adaptive directional water-filling algorithm for the throughput maximization problem. We solve the transmission completion time minimization problem by utilizing its equivalence to its throughput maximization counterpart. Next, we consider online policies. We use stochastic dynamic programming to solve for the optimal online policy that maximizes the average number of bits delivered by a deadline under stochastic fading and energy arrival processes with causal channel state feedback. We also propose near-optimal policies with reduced complexity, and numerically study their performances along with the performances of the offline and online optimal policies under various different configurations.
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paper_title: 5G on the Horizon: Key Challenges for the Radio-Access Network

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Toward the fifth generation (5G) of wireless/mobile broadband, numerous devices and networks will be interconnected and traffic demand will constantly rise. Heterogeneity will also be a feature that is expected to characterize the emerging wireless world, as mixed usage of cells of diverse sizes and access points with different characteristics and technologies in an operating environment are necessary. Wireless networks pose specific requirements that need to be fulfilled. In this respect, approaches for introducing intelligence will be investigated by the research community. Intelligence shall provide energy- and cost-efficient solutions at which a certain application/service/quality provision is achieved. Particularly, the introduction of intelligence in heterogeneous network deployments and the cloud radio-access network (RAN) is investigated. Finally, elaboration on emerging enabling technologies for applying intelligence will focus on the recent concepts of software-defined networking (SDN) and network function virtualization (NFV). This article provided an overview for delivering intelligence toward the 5G of wireless/mobile broadband by taking into account the complex context of operation and essential requirements such as QoE, energy efficiency, cost efficiency, and resource efficiency.
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paper_title: A Learning Theoretic Approach to Energy Harvesting Communication System Optimization

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A point-to-point wireless communication system in which the transmitter is equipped with an energy harvesting device and a rechargeable battery, is studied. Both the energy and the data arrivals at the transmitter are modeled as Markov processes. Delay-limited communication is considered assuming that the underlying channel is block fading with memory, and the instantaneous channel state information is available at both the transmitter and the receiver. The expected total transmitted data during the transmitter's activation time is maximized under three different sets of assumptions regarding the information available at the transmitter about the underlying stochastic processes. A learning theoretic approach is introduced, which does not assume any a priori information on the Markov processes governing the communication system. In addition, online and offline optimization problems are studied for the same setting. Full statistical knowledge and causal information on the realizations of the underlying stochastic processes are assumed in the online optimization problem, while the offline optimization problem assumes non-causal knowledge of the realizations in advance. Comparing the optimal solutions in all three frameworks, the performance loss due to the lack of the transmitter's information regarding the behaviors of the underlying Markov processes is quantified.
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paper_title: Opportunistic Wireless Energy Harvesting in Cognitive Radio Networks

paper_content:

Wireless networks can be self-sustaining by harvesting energy from ambient radio-frequency (RF) signals. Recently, researchers have made progress on designing efficient circuits and devices for RF energy harvesting suitable for low-power wireless applications. Motivated by this and building upon the classic cognitive radio (CR) network model, this paper proposes a novel method for wireless networks coexisting where low-power mobiles in a secondary network, called secondary transmitters (STs), harvest ambient RF energy from transmissions by nearby active transmitters in a primary network, called primary transmitters (PTs), while opportunistically accessing the spectrum licensed to the primary network. We consider a stochastic-geometry model in which PTs and STs are distributed as independent homogeneous Poisson point processes (HPPPs) and communicate with their intended receivers at fixed distances. Each PT is associated with a guard zone to protect its intended receiver from ST's interference, and at the same time delivers RF energy to STs located in its harvesting zone. Based on the proposed model, we analyze the transmission probability of STs and the resulting spatial throughput of the secondary network. The optimal transmission power and density of STs are derived for maximizing the secondary network throughput under the given outage-probability constraints in the two coexisting networks, which reveal key insights to the optimal network design. Finally, we show that our analytical result can be generally applied to a non-CR setup, where distributed wireless power chargers are deployed to power coexisting wireless transmitters in a sensor network.
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paper_title: Energy Efficiency Benefits of RAN-as-a-Service Concept for a Cloud-Based 5G Mobile Network Infrastructure

paper_content:

This paper focuses on energy efficiency aspects and related benefits of radio-access-network-as-a-service (RANaaS) implementation (using commodity hardware) as architectural evolution of LTE-advanced networks toward 5G infrastructure. RANaaS is a novel concept introduced recently, which enables the partial centralization of RAN functionalities depending on the actual needs as well as on network characteristics. In the view of future definition of 5G systems, this cloud-based design is an important solution in terms of efficient usage of network resources. The aim of this paper is to give a vision of the advantages of the RANaaS, to present its benefits in terms of energy efficiency and to propose a consistent system-level power model as a reference for assessing innovative functionalities toward 5G systems. The incremental benefits through the years are also discussed in perspective, by considering technological evolution of IT platforms and the increasing matching between their capabilities and the need for progressive virtualization of RAN functionalities. The description is complemented by an exemplary evaluation in terms of energy efficiency, analyzing the achievable gains associated with the RANaaS paradigm.
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paper_title: Smoothed $L_p$-Minimization for Green Cloud-RAN With User Admission Control

paper_content:

The cloud radio access network (Cloud-RAN) has recently been proposed as one of the cost-effective and energy-efficient techniques for 5G wireless networks. By moving the signal processing functionality to a single baseband unit (BBU) pool, centralized signal processing and resource allocation are enabled in cloud-RAN, thereby providing the promise of improving the energy efficiency via effective network adaptation and interference management. In this paper, we propose a holistic sparse optimization framework to design green cloud-RAN by taking into consideration the power consumption of the fronthaul links, multicast services, as well as user admission control. Specifically, we first identify the sparsity structures in the solutions of both the network power minimization and user admission control problems, which call for adaptive remote radio head (RRH) selection and user admission. However, finding the optimal sparsity structures turns out to be NP-hard, with the coupled challenges of the $\ell_0$ -norm-based objective functions and the nonconvex quadratic QoS constraints due to multicast beamforming. In contrast to the previous works on convex but nonsmooth sparsity inducing approaches, e.g., the group sparse beamforming algorithm based on the mixed $\ell_1/\ell_2$ -norm relaxation, we adopt the nonconvex but smoothed $\ell_p$ -minimization ( $0 ) approach to promote sparsity in the multicast setting, thereby enabling efficient algorithm design based on the principle of the majorization–minimization (MM) algorithm and the semidefinite relaxation (SDR) technique. In particular, an iterative reweighted- $\ell_2$ algorithm is developed, which will converge to a Karush–Kuhn–Tucker (KKT) point of the relaxed smoothed $\ell_p$ -minimization problem from the SDR technique. We illustrate the effectiveness of the proposed algorithms with extensive simulations for network power minimization and user admission control in multicast cloud-RAN.
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paper_title: Joint Optimization of Radio and Computational Resources for Multicell Mobile-Edge Computing

paper_content:

Migrating computational intensive tasks from mobile devices to more resourceful cloud servers is a promising technique to increase the computational capacity of mobile devices while saving their battery energy. In this paper, we consider an MIMO multicell system where multiple mobile users (MUs) ask for computation offloading to a common cloud server. We formulate the offloading problem as the joint optimization of the radio resources—the transmit precoding matrices of the MUs—and the computational resources—the CPU cycles/second assigned by the cloud to each MU—in order to minimize the overall users’ energy consumption, while meeting latency constraints. The resulting optimization problem is nonconvex (in the objective function and constraints). Nevertheless, in the single-user case, we are able to compute the global optimal solution in closed form. In the more challenging multiuser scenario, we propose an iterative algorithm, based on a novel successive convex approximation technique, converging to a local optimal solution of the original nonconvex problem. We then show that the proposed algorithmic framework naturally leads to a distributed and parallel implementation across the radio access points, requiring only a limited coordination/signaling with the cloud. Numerical results show that the proposed schemes outperform disjoint optimization algorithms.
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paper_title: Energy-Efficient Transmission for Wireless Energy Harvesting Nodes

paper_content:

Energy harvesting is increasingly gaining importance as a means to charge battery powered devices such as sensor nodes. Efficient transmission strategies must be developed for Wireless Energy Harvesting Nodes (WEHNs) that take into account both the availability of energy and data in the node. We consider a scenario where data and energy packets arrive to the node where the time instants and amounts of the packets are known (offline approach). In this paper, the best data transmission strategy is found for a finite battery capacity WEHN that has to fulfill some Quality of Service (QoS) constraints, as well as the energy and data causality constraints. As a result of our analysis, we can state that losing energy due to overflows of the battery is inefficient unless there is no more data to transmit and that the problem may not have a feasible solution. Finally, an algorithm that computes the data transmission curve minimizing the total transmission time that satisfies the aforementioned constraints has been developed.
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paper_title: Cooperative Non-Orthogonal Multiple Access with Simultaneous Wireless Information and Power Transfer

paper_content:

In this paper, the application of simultaneous wireless information and power transfer (SWIPT) to nonorthogonal multiple access (NOMA) networks in which users are spatially randomly located is investigated. A new co-operative SWIPT NOMA protocol is proposed, in which near NOMA users that are close to the source act as energy harvesting relays to help far NOMA users. Since the locations of users have a significant impact on the performance, three user selection schemes based on the user distances from the base station are proposed. To characterize the performance of the proposed selection schemes, closed-form expressions for the outage probability and system throughput are derived. These analytical results demonstrate that the use of SWIPT will not jeopardize the diversity gain compared to the conventional NOMA. The proposed results confirm that the opportunistic use of node locations for user selection can achieve low outage probability and deliver superior throughput in comparison to the random selection scheme.
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paper_title: Energy Harvesting Wireless Communications: A Review of Recent Advances

paper_content:

This paper summarizes recent contributions in the broad area of energy harvesting wireless communications. In particular, we provide the current state of the art for wireless networks composed of energy harvesting nodes, starting from the information-theoretic performance limits to transmission scheduling policies and resource allocation, medium access, and networking issues. The emerging related area of energy transfer for self-sustaining energy harvesting wireless networks is considered in detail covering both energy cooperation aspects and simultaneous energy and information transfer. Various potential models with energy harvesting nodes at different network scales are reviewed, as well as models for energy consumption at the nodes.
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paper_title: Energy Cooperation in Energy Harvesting Communications

paper_content:

In energy harvesting communications, users transmit messages using energy harvested from nature during the course of communication. With an optimum transmit policy, the performance of the system depends only on the energy arrival profiles. In this paper, we introduce the concept of energy cooperation, where a user wirelessly transmits a portion of its energy to another energy harvesting user. This enables shaping and optimization of the energy arrivals at the energy-receiving node, and improves the overall system performance, despite the loss incurred in energy transfer. We consider several basic multi-user network structures with energy harvesting and wireless energy transfer capabilities: relay channel, two-way channel and multiple access channel. We determine energy management policies that maximize the system throughput within a given duration using a Lagrangian formulation and the resulting KKT optimality conditions. We develop a two-dimensional directional water-filling algorithm which optimally controls the flow of harvested energy in two dimensions: in time (from past to future) and among users (from energy-transferring to energy-receiving) and show that a generalized version of this algorithm achieves the boundary of the capacity region of the two-way channel.
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paper_title: Performance of the Wideband Massive Uplink MIMO with One-Bit ADCs

paper_content:

Analog-to-digital converters (ADCs) consume a significant part of the total power in a massive MIMO base station. One-bit ADCs are one way to reduce power consumption. This paper presents an analysis of the spectral efficiency of single-carrier and OFDM transmission in massive MIMO systems that use one-bit ADCs. A closed-form achievable rate is derived for a wideband system with a large number of channel taps, assuming linear channel estimation and symbol detection. Quantization results in two types of error in the symbol detection. The circularly symmetric error becomes Gaussian in massive MIMO and vanishes as the number of antennas grows. The amplitude distortion, which severely degrades the performance of OFDM, is caused by variations in received interference energy between symbol durations. As the number of channel taps grows, the amplitude distortion vanishes and OFDM has the same performance as single-carrier transmission. A main conclusion of this paper is that wideband massive MIMO systems work well with one-bit ADCs.
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paper_title: Capacity Analysis of One-Bit Quantized MIMO Systems with Transmitter Channel State Information

paper_content:

With bandwidths on the order of a gigahertz in emerging wireless systems, high-resolution analog-to-digital convertors (ADCs) become a power consumption bottleneck. One solution is to employ low resolution one-bit ADCs. In this paper, we analyze the flat fading multiple-input multiple-output (MIMO) channel with one-bit ADCs. Channel state information is assumed to be known at both the transmitter and receiver. For the multiple-input single-output channel, we derive the exact channel capacity. For the single-input multiple-output and MIMO channel, the capacity at infinite signal-to-noise ratio (SNR) is found. We also derive upper bound at finite SNR, which is tight when the channel has full row rank. In addition, we propose an efficient method to design the input symbols to approach the capacity achieving solution. We incorporate millimeter wave channel characteristics and find the bounds on the infinite SNR capacity. The results show how the number of paths and number of receive antennas impact the capacity.
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paper_title: Large-scale antenna systems with hybrid analog and digital beamforming for millimeter wave 5G

paper_content:

With the severe spectrum shortage in conventional cellular bands, large-scale antenna systems in the mmWave bands can potentially help to meet the anticipated demands of mobile traffic in the 5G era. There are many challenging issues, however, regarding the implementation of digital beamforming in large-scale antenna systems: complexity, energy consumption, and cost. In a practical large-scale antenna deployment, hybrid analog and digital beamforming structures can be important alternative choices. In this article, optimal designs of hybrid beamforming structures are investigated, with the focus on an N (the number of transceivers) by M (the number of active antennas per transceiver) hybrid beamforming structure. Optimal analog and digital beamforming designs in a multi-user beamforming scenario are discussed. Also, the energy efficiency and spectrum efficiency of the N × M beamforming structure are analyzed, including their relationship at the green point (i.e., the point with the highest energy efficiency) on the energy efficiency-spectrum efficiency curve, the impact of N on the energy efficiency performance at a given spectrum efficiency value, and the impact of N on the green point energy efficiency. These results can be conveniently utilized to guide practical LSAS design for optimal energy/ spectrum efficiency trade-off. Finally, a reference signal design for the hybrid beamform structure is presented, which achieves better channel estimation performance than the method solely based on analog beamforming. It is expected that large-scale antenna systems with hybrid beamforming structures in the mmWave band can play an important role in 5G.
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paper_title: Energy-efficient hybrid precoding based on successive interference cancelation for millimeter-wave massive MIMO systems

paper_content:

Millimeter-wave massive MIMO usually utilizes the hybrid precoding to overcome the serious signal attenuation, where only a small number of RF chains is required. However, most of hybrid precoding schemes consider the complicated full-connected architecture. In this paper, we focus on the more energy-efficient sub-connected architecture, and propose a low-complexity hybrid precoding based on successive interference cancelation (SIC). The basic idea of SIC-based hybrid precoding is to decompose the total capacity optimization problem into a series of sub-problems, each of which only considers one sub-antenna array. Then, we can optimize the capacity of each sub-antenna array one by one until the last sub-antenna array is considered. Simulation results verify that SIC-based hybrid precoding can achieve the near-optimal performance.
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paper_title: Throughput Maximization for the Gaussian Relay Channel with Energy Harvesting Constraints

paper_content:

This paper considers the use of energy harvesters, instead of conventional time-invariant energy sources, in wireless cooperative communication. For the purpose of exposition, we study the classic three-node Gaussian relay channel with decode-and-forward (DF) relaying, in which the source and relay nodes transmit with power drawn from energy-harvesting (EH) sources. Assuming a deterministic EH model under which the energy arrival time and the harvested amount are known prior to transmission, the throughput maximization problem over a finite horizon of N transmission blocks is investigated. In particular, two types of data traffic with different delay constraints are considered: delay-constrained (DC) traffic (for which only one-block decoding delay is allowed at the destination) and no-delay-constrained (NDC) traffic (for which arbitrary decoding delay up to N blocks is allowed). For the DC case, we show that the joint source and relay power allocation over time is necessary to achieve the maximum throughput, and propose an efficient algorithm to compute the optimal power profiles. For the NDC case, although the throughput maximization problem is non-convex, we prove the optimality of a separation principle for the source and relay power allocation problems, based upon which a two-stage power allocation algorithm is developed to obtain the optimal source and relay power profiles separately. Furthermore, we compare the DC and NDC cases, and obtain the sufficient and necessary conditions under which the NDC case performs strictly better than the DC case. It is shown that NDC transmission is able to exploit a new form of diversity arising from the independent source and relay energy availability over time in cooperative communication, termed "energy diversity", even with time-invariant channels.
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paper_title: Renewable energy in cellular networks: A survey

paper_content:

In recent years a lot of research work was dedicated to energy efficiency in cellular networks. An emerging field of interest in that direction is the use of renewable energy sources such as wind and solar - a type of energy that is bound to increase and develop. In this paper we survey the existing works and present the fundamental principles and motivations necessary for a thorough understanding of the usage of renewable energy in cellular networks. Furthermore, we introduce a reference model for renewable energy base station (REBS) and provide analysis of its components. The synthesis of dedicated REBS algorithms, system architectures, deployment strategies and evaluation metrics provides comprehensive overview and helps identify the perspectives in this promising research field.
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paper_title: A general framework for the optimization of energy harvesting communication systems with battery imperfections

paper_content:

Energy harvesting has emerged as a powerful technology for complementing current battery-powered communication systems in order to extend their lifetime. In this paper a general framework is introduced for the optimization of communication systems in which the transmitter is able to harvest energy from its environment. Assuming that the energy arrival process is known non-causally at the transmitter, the structure of the optimal transmission scheme, which maximizes the amount of transmitted data by a given deadline, is identified. Our framework includes models with continuous energy arrival as well as battery constraints. A battery that suffers from energy leakage is studied further, and the optimal transmission scheme is characterized for a constant leakage rate.
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paper_title: Energy Efficiency and Interference Neutralization in Two-Hop MIMO Interference Channels

paper_content:

The issue of energy-aware resource allocation in an amplify-and-forward (AF) relay-assisted multiple-antenna interference channel (IC) is considered. A novel interference neutralization (IN) scheme is proposed for relay design and, based on the IN relay matrix design, two algorithms are developed to jointly allocate the users' transmit powers, beamforming (BF) and receive filters. The first algorithm considers a competitive scenario and employs a noncooperative game-theoretic approach to maximize the individual energy efficiency (EE) of each communication link, defined as the ratio of the achievable rate over the consumed power. The resulting algorithm converges to a unique fixed point, has limited complexity, and can be implemented in a distributed fashion. The second algorithm employs fractional programming tools and sequential convex optimization to centrally allocate the users' transmit powers, BF, and receive filters for global energy efficiency (GEE) maximization. The resulting algorithm is guaranteed to converge and has limited computational complexity. Numerical results show that the competitive IN design achieves virtually the same performance as the cooperative design if IN is feasible, while the gap is small if perfect IN is not achievable.
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paper_title: Energy Efficiency in MIMO Underlay and Overlay Device-to-Device Communications and Cognitive Radio Systems

paper_content:

This paper addresses the problem of resource allocation for systems in which a primary and a secondary link share the available spectrum by an underlay or overlay approach. After observing that such a scenario models both cognitive radio and D2D communications, we formulate the problem as the maximization of the secondary energy efficiency subject to a minimum rate requirement for the primary user. This leads to challenging nonconvex, fractional problems. In the underlay scenario, we obtain the global solution by means of a suitable reformulation. In the overlay scenario, two algorithms are proposed. The first one yields a resource allocation fulfilling the first-order optimality conditions of the resource allocation problem, by solving a sequence of easier fractional programs. The second one enjoys a weaker optimality claim, but an even lower computational complexity. Numerical results demonstrate the merits of the proposed algorithms both in terms of energy-efficient performance and complexity, also showing that the two proposed algorithms for the overlay scenario perform very similarly, despite the different complexity.
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paper_title: Energy-Efficient Power Control: A Look at 5G Wireless Technologies

paper_content:

This paper develops power control algorithms for energy efficiency (EE) maximization (measured in bit/Joule) in wireless networks. Unlike previous related works, minimum-rate constraints are imposed and the signal-to-interference-plus-noise ratio takes a more general expression, which allows one to encompass some of the most promising 5G candidate technologies. Both network-centric and user-centric EE maximizations are considered. In the network-centric scenario, the maximization of the global EE and the minimum EE of the network is performed. Unlike previous contributions, we develop centralized algorithms that are guaranteed to converge, with affordable computational complexity, to a Karush–Kuhn–Tucker point of the considered non-convex optimization problems. Moreover, closed-form feasibility conditions are derived. In the user-centric scenario, game theory is used to study the equilibria of the network and to derive convergent power control algorithms, which can be implemented in a fully decentralized fashion. Both scenarios above are studied under the assumption that single or multiple resource blocks are employed for data transmission. Numerical results assess the performance of the proposed solutions, analyzing the impact of minimum-rate constraints, and comparing the network-centric and user-centric approaches.
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paper_title: Energy-Efficient Scheduling and Power Allocation in Downlink OFDMA Networks With Base Station Coordination

paper_content:

This paper addresses the problem of energy-efficient resource allocation in the downlink of a cellular OFDMA system. Three definitions of the energy efficiency are considered for system design, accounting for both the radiated and the circuit power. User scheduling and power allocation are optimized across a cluster of coordinated base stations with a constraint on the maximum transmit power (either per subcarrier or per base station). The asymptotic noise-limited regime is discussed as a special case. %The performance of both an isolated and a non-isolated cluster of coordinated base stations is examined in the numerical experiments. Results show that the maximization of the energy efficiency is approximately equivalent to the maximization of the spectral efficiency for small values of the maximum transmit power, while there is a wide range of values of the maximum transmit power for which a moderate reduction of the data rate provides a large saving in terms of dissipated energy. Also, the performance gap among the considered resource allocation strategies reduces as the out-of-cluster interference increases.
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paper_title: Precoding for Full Duplex Multiuser MIMO Systems: Spectral and Energy Efficiency Maximization

paper_content:

We consider data transmissions in a full duplex (FD) multiuser multiple-input multiple-output (MU-MIMO) system, where a base station (BS) bidirectionally communicates with multiple users in the downlink (DL) and uplink (UL) channels on the same system resources. The system model of consideration has been thought to be impractical due to the self-interference (SI) between transmit and receive antennas at the BS. Interestingly, recent advanced techniques in hardware design have demonstrated that the SI can be suppressed to a degree that possibly allows for FD transmission. This paper goes one step further in exploring the potential gains in terms of the spectral efficiency (SE) and energy efficiency (EE) that can be brought by the FD MU-MIMO model. Toward this end, we propose low-complexity designs for maximizing the SE and EE, and evaluate their performance numerically. For the SE maximization problem, we present an iterative design that obtains a locally optimal solution based on a sequential convex approximation method. In this way, the nonconvex precoder design problem is approximated by a convex program at each iteration. Then, we propose a numerical algorithm to solve the resulting convex program based on the alternating and dual decomposition approaches, where analytical expressions for precoders are derived. For the EE maximization problem, using the same method, we first transform it into a concave-convex fractional program, which then can be reformulated as a convex program using the parametric approach. We will show that the resulting problem can be solved similarly to the SE maximization problem. Numerical results demonstrate that, compared to a half duplex system, the FD system of interest with the proposed designs achieves a better SE and a slightly smaller EE when the SI is small.
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Title: A Survey of Energy-Efficient Techniques for 5G Networks and Challenges Ahead

Section 1: INTRODUCTION
Description 1: This section introduces the primary concerns regarding energy consumption in wireless communication systems, emphasizing the need for energy efficiency in designing 5G networks.

Section 2: RESOURCE ALLOCATION
Description 2: This section discusses different techniques and mathematical tools for energy-efficient resource allocation in 5G networks, comparing them with traditional throughput-optimized communication methods.

Section 3: NETWORK PLANNING AND DEPLOYMENT
Description 3: This section explores various strategies for network densification and infrastructure planning, including dense heterogeneous networks and massive MIMO, to enhance energy efficiency.

Section 4: OFFLOADING TECHNIQUES
Description 4: This section outlines various offloading strategies, such as D2D communications, VLC, local caching, and mmWave cellular, aimed at improving network capacity and energy efficiency.

Section 5: ENERGY HARVESTING AND TRANSFER
Description 5: This section reviews methods of harvesting energy from the environment and radio-frequency signals, addressing the challenges posed by the randomness of energy availability.

Section 6: HARDWARE SOLUTIONS
Description 6: This section covers energy-efficient hardware strategies, including the green design of RF chains, simplified transmitter/receiver architectures, and cloud-based implementations of RAN.

Section 7: FUTURE RESEARCH CHALLENGES
Description 7: This section identifies the gaps in current research and suggests holistic approaches, interference and randomness management, emerging techniques, and new energy models for future studies.

Section 8: CONCLUSIONS
Description 8: This section concludes the survey by summarizing the importance of energy efficiency in 5G networks and highlighting the persistent challenges and prospects for further research and development.