A Survey on Dynamic Spectrum Access Techniques in Cognitive Radio Networks
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paper_title: Spectrum auction framework for access allocation in cognitive radio networks

paper_content:

In cognitive radio networks, there are two categories of networks on different channels: primary networks, which have high-priority access, and secondary networks, which have low-priority access. We develop an auction-based framework that allows networks to bid for primary and secondary access based on their utilities and traffic demands. The bids are used to solve the access allocation problem, which is that of selecting the primary and secondary networks on each channel either to maximize the auctioneer's revenue or to maximize the social welfare of the bidding networks, while enforcing incentive compatibility. We first consider the case when the bids of a network depend on which other networks it will share channels with. When there is only one secondary network on each channel, we design an optimal polynomial-time algorithm for the access allocation problem based on reduction to a maximum matching problem in weighted graphs. When there can be two or more secondary networks on a channel, we show that the optimal access allocation problem is NP-complete. Next, we consider the case when the bids of a network are independent of which other networks it will share channels with. We design a polynomial-time dynamic programming algorithm to optimally solve the access allocation problem when the number of possible cardinalities of the set of secondary networks on a channel is upper-bounded. Finally, we design a polynomial-time algorithm that approximates the access allocation problem within a factor of 2 when the above upper bound does not exist.
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paper_title: CRAHNs : Cognitive radio ad hoc networks

paper_content:

Cognitive radio (CR) technology is envisaged to solve the problems in wireless networks resulting from the limited available spectrum and the inefficiency in the spectrum usage by exploiting the existing wireless spectrum opportunistically. CR networks, equipped with the intrinsic capabilities of the cognitive radio, will provide an ultimate spectrum-aware communication paradigm in wireless communications. CR networks, however, impose unique challenges due to the high fluctuation in the available spectrum as well as diverse quality-of-service (QoS) requirements. Specifically, in cognitive radio ad hoc networks (CRAHNs), the distributed multi-hop architecture, the dynamic network topology, and the time and location varying spectrum availability are some of the key distinguishing factors. In this paper, intrinsic properties and current research challenges of the CRAHNs are presented. First, novel spectrum management functionalities such as spectrum sensing, spectrum sharing, and spectrum decision, and spectrum mobility are introduced from the viewpoint of a network requiring distributed coordination. A particular emphasis is given to distributed coordination between CR users through the establishment of a common control channel. Moreover, the influence of these functions on the performance of the upper layer protocols, such as the network layer, and transport layer protocols are investigated and open research issues in these areas are also outlined. Finally, a new direction called the commons model is explained, where CRAHN users may independently regulate their own operation based on pre-decided spectrum etiquette.
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paper_title: Resource Pricing with Primary Service Guarantees in Cognitive Radio Networks: A Stackelberg Game Approach

paper_content:

Cognitive Radio (CR) is envisioned as one of the most promising technologies to solve the problem of spectrum scarcity. A critical problem that limits the development of CR technology is the absence of a mechanism efficient enough to allocate under-utilized spectrum resource from primary users (PUs) to multiple secondary users (SUs) [1], [2]. Toward this end, we adopt "Game Theory" [3], [4] as our modeling tool. Spectrum users can be modeled as selfish, rational players in this spectrum selling game with PUs as spectrum sellers and SUs as buyers. Considering that PUs always know more about the "market" than SUs and marking prices should always be ahead of purchasing, we use a Stackelberg Game to analyze the pricing and allocation process of PUs and SUs under the circumstance of information asymmetry. A parameter I is later introduced to measure the negative impact from SUs to PUs. If given a predefined value of I, a feasible pricing region can be found to guarantee the primary service. Finally, a contract between PUs and SUs is proposed as a counterpart of the information asymmetry and a utility increase of SUs is observed when the contract is valid.
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paper_title: A Cooperative Multiagent Based Spectrum Sharing

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A major issue in recent wireless networks is the static utilization and allocation of the available spectrum. An effective solution to this problem is to detect the empty spectrum portions using cognitive radio devices and to share them with the neighboring users, in a dynamic and distributed manner. However, since nodes generally have limited knowledge about their environment, we suggest that cooperative behavior can provide them with the necessary information in order to solve the global issues. To this extend, we develop a novel approach for spectrum allocation using multiagent system cooperation that enables cognitive radio (or secondary user) devices to utilize the amount of available spectrum, dynamically and opportunistically. The key aspect of our design is the deployment of agents on each of the primary and secondary user devices that cooperate in order to have a better use of the spectrum. For cooperation, contract net protocol is considered, allowing spectrum to be dynamically allocated by having a series of exchange of messages amongst the devices. Simulation results show that our approach achieves up to 80% of the whole utility within the span of few messages, and provides an effective mechanism for distributed spectrum allocation.
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paper_title: Utilization of cooperative multi-agent systems for spectrum sharing in cognitive radio networks

paper_content:

Static spectrum allocation is a major problem in recent wireless networks. This scarcity problem is temporary and can be alleviated if the spectrum access is performed dynamically. Cognitive radio (CR) is an important new technology which addresses dynamic spectrum access challenges in detail. These challenges include efficient allocation of spectrum for primary (or licensed) and CR (or secondary) users in order to increase spectrum usage and to avoid user conflicts. Therefore, in this research we are interested in developing novel solutions for dynamic and efficient spectrum access under (1) licensed bands where CR users attempt to use the spec-trum by coexisting with the primary users and (2) unlicensed bands where the CR users try to access the spectrum by avoiding conflicts with their neighbors. In our first proposal, we deploy agents over each primary and CR users which allow them to work cooperatively in order to make spectrum access agreements. The simulation results show that our approach achieves good performance in terms of spectrum access, sustaining lower communication overhead. Our second proposal focuses on unlicensed spectrum access where spectrum can be viewed as an open ‘pool’ and no user has an exclusive license for spectrum access. Using multi-agent system, the CR users cooperate and they form several coalitions. These types of coalitions can provide a less-conflicted access as the agents mutually agree for spectrum sharing. The important comparisons between analytical and simulation results in terms of blocking probability verify the relevance of our approach in CR context
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paper_title: Dynamic spectrum access in open spectrum wireless networks

paper_content:

One of the reasons for the limitation of bandwidth in current generation wireless networks is the spectrum policy of the Federal Communications Commission (FCC). But, with the spectrum policy reform, open spectrum wireless networks, and spectrum agile radios are set to drive next general wireless networks. In this paper, we investigate continuous-time Markov models for dynamic spectrum access in open spectrum wireless networks. Both queueing and no queueing cases are considered. Analytical results are derived based on the Markov models. A random access protocol is proposed that is shown to achieve airtime fairness. A distributed version of this protocol that uses only local information is also proposed based on homo egualis anthropological model. Inequality aversion by the radio systems to achieve fairness is captured by this model. These protocols are then extended to spectrum agile radios. Extensive simulation results are presented to compare the performances of fixed versus agile radios.
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paper_title: Revenue generation for truthful spectrum auction in dynamic spectrum access

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Spectrum is a critical yet scarce resource and it has been shown that dynamic spectrum access can significantly improve spectrum utilization. To achieve this, it is important to incentivize the primary license holders to open up their under-utilized spectrum for sharing. In this paper we present a secondary spectrum market where a primary license holder can sell access to its unused or under-used spectrum resources in the form of certain fine-grained spectrum-space-time unit. Secondary wireless service providers can purchase such contracts to deploy new service, enhance their existing service, or deploy ad hoc service to meet flash crowds demand. Within the context of this market, we investigate how to use auction mechanisms to allocate and price spectrum resources so that the primary license holder's revenue is maximized. We begin by classifying a number of alternative auction formats in terms of spectrum demand. We then study a specific auction format where secondary wireless service providers have demands for fixed locations (cells). We propose an optimal auction based on the concept of virtual valuation. Assuming the knowledge of valuation distributions, the optimal auction uses the Vickrey-Clarke-Groves (VCG) mechanism to maximize the expected revenue while enforcing truthfulness. To reduce the computational complexity, we further design a truthful suboptimal auction with polynomial time complexity. It uses a monotone allocation and critical value payment to enforce truthfulness. Simulation results show that this suboptimal auction can generate stable expected revenue.
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paper_title: Aggregated interference control for cognitive radio networks based on multi-agent learning

paper_content:

This paper deals with the problem of aggregated interference generated by multiple cognitive radios (CR) at the receivers of primary (licensed) users. In particular, we consider a secondary CR system based on the IEEE 802.22 standard for wireless regional area networks (WRAN), and we model it as a multi-agent system where the multiple agents are the different secondary base stations in charge of controlling the different secondary cells. We propose a solution for the aggregated interference problem based on a form of real-time multi-agent reinforcement learning known as decentralized Qlearning, so that the multi-agent system is designed to learn an optimal policy by directly interacting with the surrounding environment in a distributed fashion. Simulation results reveal that the proposed approach is able to fulfil the primary users interference constraints, without introducing signalling overhead in the system.
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paper_title: Enhancing Network Performance in Distributed Cognitive Radio Networks using Single-Agent and Multi-Agent Reinforcement Learning

paper_content:

Cognitive Radio (CR) is a next-generation wireless communication system that enables unlicensed users to exploit underutilized licensed spectrum to optimize the utilization of the overall radio spectrum. A Distributed Cognitive Radio Network (DCRN) is a distributed wireless network established by a number of unlicensed users in the absence of fixed network infrastructure such as a base station. Context awareness and intelligence are the capabilities that enable each unlicensed user to observe and carry out its own action as part of the joint action on its operating environment for network-wide performance enhancement. These capabilities can be applied in various application schemes in CR networks such as Dynamic Channel Selection (DCS), congestion control, and scheduling. In this paper, we apply Reinforcement Learning (RL), including single-agent and multi-agent approaches, to achieve context awareness and intelligence. Firstly, we show that the RL approach achieves a joint action that provides better network-wide performance in respect to DCS in DCRNs. The multi-agent approach is shown to provide higher levels of stability compared to the single-agent approach. Secondly, we show that RL achieves high level of fairness. Thirdly, we show the effects of network density and various essential parameters in RL on the network-wide performance.
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paper_title: Multiagent Based Spectrum Sharing Using Petri Nets

paper_content:

This paper presents a cooperative framework for dynamic spectrum access in cognitive radio networks, where the cognitive radio devices may use the currently unutilized spectrum dynamically and opportunistically. The proposed solution works on the principle of multiagent system that allows the cooperation amongst several participating devices. The key aspect of our design is the deployment of agents on each of the primary and cognitive radio device that cooperates in order to have a better and dynamic use of the spectrum. For cooperation, contract net protocol is considered allowing spectrum to be dynamically allocated by having a series of exchange of messages. Due to the concurrent, distributed and autonomous nature of our approach, Petri nets are adopted to model the behavior of cooperative framework. Based on Petri nets, we study the internal message passing and spectrum allocation mechanism between the participating primary and cognitive radio users and identify the information needed by the agents to make cooperative decisions. Then, using empirical results, we show that our approach achieves up to 80% of the whole utility within the span of few messages, and provides an effective mechanism for distributed spectrum allocation.
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paper_title: Spectrum Sharing in Cognitive Radio Networks—An Auction-Based Approach

paper_content:

Cognitive radio is emerging as a promising technique to improve the utilization of the radio frequency spectrum. In this paper, we consider the problem of spectrum sharing among primary (or ?licensed?) users (PUs) and secondary (or ?unlicensed?) users (SUs). We formulate the problem based on bandwidth auction, in which each SU makes a bid for the amount of spectrum and each PU may assign the spectrum among the SUs by itself according to the information from the SUs without degrading its own performance. We show that the auction is a noncooperative game and that Nash equilibrium (NE) can be its solution. We first consider a single-PU network to investigate the existence and uniqueness of the NE and further discuss the fairness among the SUs under given conditions. Then, we present a dynamic updating algorithm in which each SU achieves NE in a distributed manner. The stability condition of the dynamic behavior for this spectrum-sharing scheme is studied. The discussion is generalized to the case in which there are multiple PUs in the network, where the properties of the NE are shown under appropriate conditions. Simulations were used to evaluate the system performance and verify the effectiveness of the proposed algorithm.
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paper_title: Opportunistic Spectrum Access in Cognitive Radio Networks

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Driven by regulatory initiatives and radio technology advances, opportunistic spectrum access has the potential to mitigate spectrum scarcity and meet the increasing demand for spectrum. In this paper, we consider a scenario where secondary users can opportunistically access unused spectrum vacated by idle primaries. We introduce two metrics to protect primary performance, namely collision probability and overlapping time. We present three spectrum access schemes using different sensing, back-off, and transmission mechanisms. We show that they achieve indistinguishable secondary performance under given primary constraints. We provide closed form analysis on secondary user performance, present a tight capacity upper bound, and reveal the impact of various design options, such as sensing, packet length distribution, back-off time, packet overhead, and grouping. Our work sheds light on the fundamental properties and design criteria on opportunistic spectrum access.
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paper_title: Cognitive Radio Channel Allocation Using Auction Mechanisms

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We adopt the auction mechanisms into the dynamic channel allocation of cognitive radio networks. Under auction schemes, users bid the transmission time slots to gain access to the licensed channel. Their bids accumulate throughout the repeated bidding process over time, and they pay the "bill" at the end of the time frame in the form of out-band sensing. By doing so, we allocate the channel to the user who values it most, and impose a responsibility for out-band sensing which is split up among users according to their aggregate winning bids. We study the allocation under both first and second price sealed-bid auctions and find that they yield similar outcomes in terms of throughput and efficiency. We also develop two auction-based improvement schemes to address the traffic issue in secondary nodes, and the system performance receives a significant boost as a result.
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paper_title: Auction-Based Agent Negotiation in Cognitive Radio Ad Hoc Networks

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The explosive growth of wireless services in recent years illustrates the growing demand for communications, so the spectrum becomes more congested. We know that static spectrum allocation is a major problem in wireless networks. Generally, these allocations lead to an inefficient use of spectrum. To solve the problem of congestion, cognitive radio networks use dynamic spectrum access. In this paper, we use a technique based on auctions theory known for its simplicity and facilitates the allocation of scarce resources.
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paper_title: Spectrum Trading in Cognitive Radio Networks: An Agent-Based Model under Demand Uncertainty

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In this paper, we propose an agent-based spectrum trading model, where an agent can play a third-party role in the spectrum trading process. Providing service to Secondary Users (SUs) with spectrum bought from Primary Users (PUs), the agent can make profits during the process by providing service to secondary users. During each trading period, the agent has to decide how much spectrum it should lease from PUs and what price it should charge SUs. Therefore, the most significant challenge to implement this spectrum trading model is finding the most profitable strategy for agent(s). We address this challenge under two scenarios in which: 1) a single agent and 2) multiple agents. Instead of quantifying SUs' spectrum demand by a deterministic function of price, we take the randomness of secondary users' demand or demand uncertainty into consideration. To the best of our knowledge, this is the first solution to agent-based spectrum trading considering demand uncertainty.
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paper_title: Coalitional Games in Partition Form for Joint Spectrum Sensing and Access in Cognitive Radio Networks

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Unlicensed secondary users (SUs) in cognitive radio networks are subject to an inherent tradeoff between spectrum sensing and spectrum access. Although each SU has an incentive to sense the primary user (PU) channels for locating spectrum holes, this exploration of the spectrum can come at the expense of a shorter transmission time, and, hence, a possibly smaller capacity for data transmission. This paper investigates the impact of this tradeoff on the cooperative strategies of a network of SUs that seek to cooperate in order to improve their view of the spectrum (sensing), reduce the possibility of interference among each other, and improve their transmission capacity (access). The problem is modeled as a coalitional game in partition form and an algorithm for coalition formation is proposed. Using the proposed algorithm, the SUs can make individual distributed decisions to join or leave a coalition while maximizing their utilities which capture the average time spent for sensing as well as the capacity achieved while accessing the spectrum. It is shown that, by using the proposed algorithm, the SUs can self-organize into a network partition composed of disjoint coalitions, with the members of each coalition cooperating to jointly optimize their sensing and access performance. Simulation results show the performance improvement that the proposed algorithm yields with respect to the noncooperative case. The results also show how the algorithm allows the SUs to self-adapt to changes in the environment such as changes in the traffic of the PUs, or slow mobility.
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paper_title: Cognitive radio: brain-empowered wireless communications

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Cognitive radio is viewed as a novel approach for improving the utilization of a precious natural resource: the radio electromagnetic spectrum. The cognitive radio, built on a software-defined radio, is defined as an intelligent wireless communication system that is aware of its environment and uses the methodology of understanding-by-building to learn from the environment and adapt to statistical variations in the input stimuli, with two primary objectives in mind: /spl middot/ highly reliable communication whenever and wherever needed; /spl middot/ efficient utilization of the radio spectrum. Following the discussion of interference temperature as a new metric for the quantification and management of interference, the paper addresses three fundamental cognitive tasks. 1) Radio-scene analysis. 2) Channel-state estimation and predictive modeling. 3) Transmit-power control and dynamic spectrum management. This work also discusses the emergent behavior of cognitive radio.
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paper_title: Toward cognitive radio handover management based on social agent technology for spectrum efficiency performance improvement of cellular systems

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Interference and delay are considered as the main reasons limiting the capacity and increasing the new call blocking probability in the cellular systems. The Probability of handover failure is considered a common criterion for performance evaluation of handovers in cellular systems. In this paper we discuss and analyze cognitive radio handover managements based on social agent technology in cellular systems.
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paper_title: Cooperative Communications for Cognitive Radio Networks

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Cognitive radio is an exciting emerging technology that has the potential of dealing with the stringent requirement and scarcity of the radio spectrum. Such revolutionary and transforming technology represents a paradigm shift in the design of wireless systems, as it will allow the agile and efficient utilization of the radio spectrum by offering distributed terminals or radio cells the ability of radio sensing, self-adaptation, and dynamic spectrum sharing. Cooperative communications and networking is another new communication technology paradigm that allows distributed terminals in a wireless network to collaborate through some distributed transmission or signal processing so as to realize a new form of space diversity to combat the detrimental effects of fading channels. In this paper, we consider the application of these technologies to spectrum sensing and spectrum sharing. One of the most important challenges for cognitive radio systems is to identify the presence of primary (licensed) users over a wide range of spectrum at a particular time and specific geographic location. We consider the use of cooperative spectrum sensing in cognitive radio systems to enhance the reliability of detecting primary users. We shall describe spectrum sensing for cognitive radios and propose robust cooperative spectrum sensing techniques for a practical framework employing cognitive radios. We also investigate cooperative communications for spectrum sharing in a cognitive wireless relay network. To exploit the maximum spectrum opportunities, we present a cognitive space-time-frequency coding technique that can opportunistically adjust its coding structure by adapting itself to the dynamic spectrum environment.
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paper_title: Utilization of cooperative multi-agent systems for spectrum sharing in cognitive radio networks

paper_content:

Static spectrum allocation is a major problem in recent wireless networks. This scarcity problem is temporary and can be alleviated if the spectrum access is performed dynamically. Cognitive radio (CR) is an important new technology which addresses dynamic spectrum access challenges in detail. These challenges include efficient allocation of spectrum for primary (or licensed) and CR (or secondary) users in order to increase spectrum usage and to avoid user conflicts. Therefore, in this research we are interested in developing novel solutions for dynamic and efficient spectrum access under (1) licensed bands where CR users attempt to use the spec-trum by coexisting with the primary users and (2) unlicensed bands where the CR users try to access the spectrum by avoiding conflicts with their neighbors. In our first proposal, we deploy agents over each primary and CR users which allow them to work cooperatively in order to make spectrum access agreements. The simulation results show that our approach achieves good performance in terms of spectrum access, sustaining lower communication overhead. Our second proposal focuses on unlicensed spectrum access where spectrum can be viewed as an open ‘pool’ and no user has an exclusive license for spectrum access. Using multi-agent system, the CR users cooperate and they form several coalitions. These types of coalitions can provide a less-conflicted access as the agents mutually agree for spectrum sharing. The important comparisons between analytical and simulation results in terms of blocking probability verify the relevance of our approach in CR context
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paper_title: Decentralized dynamic spectrum access for cognitive radios: cooperative design of a non-cooperative game

paper_content:

We consider dynamic spectrum access among cognitive radios from an adaptive, game theoretic learning perspective. Spectrum-agile cognitive radios compete for channels temporarily vacated by licensed primary users in order to satisfy their own demands while minimizing interference. For both slowly varying primary user activity and slowly varying statistics of "fast" primary user activity, we apply an adaptive regret based learning procedure which tracks the set of correlated equilibria of the game, treated as a distributed stochastic approximation. This procedure is shown to perform very well compared with other similar adaptive algorithms. We also estimate channel contention for a simple CSMA channel sharing scheme.
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paper_title: Dynamic spectrum access in open spectrum wireless networks

paper_content:

One of the reasons for the limitation of bandwidth in current generation wireless networks is the spectrum policy of the Federal Communications Commission (FCC). But, with the spectrum policy reform, open spectrum wireless networks, and spectrum agile radios are set to drive next general wireless networks. In this paper, we investigate continuous-time Markov models for dynamic spectrum access in open spectrum wireless networks. Both queueing and no queueing cases are considered. Analytical results are derived based on the Markov models. A random access protocol is proposed that is shown to achieve airtime fairness. A distributed version of this protocol that uses only local information is also proposed based on homo egualis anthropological model. Inequality aversion by the radio systems to achieve fairness is captured by this model. These protocols are then extended to spectrum agile radios. Extensive simulation results are presented to compare the performances of fixed versus agile radios.
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paper_title: Dynamic Spectrum Access in Cognitive Radio Wireless Networks

paper_content:

Cognitive radio wireless networks is an emerging communication paradigm to effectively address spectrum scarcity challenge. Spectrum sharing enables the secondary unlicensed system to dynamically access the licensed frequency bands in the primary system without any modification to the devices, terminals, services and networks in the primary system. In this paper, we propose and analyze new dynamic spectrum access schemes in the absence or presence of buffering mechanism for the cognitive secondary subscriber (SU). A Markov approach is developed to analyze the proposed spectrum sharing policies with generalized bandwidth size in both primary system and secondary system. Performance metrics for SU are developed with respect to blocking probability, interrupted probability, forced termination probability, non-completion probability and waiting time. Numerical examples are presented to explore the impact of key systems parameters like the traffic load on the performance metrics. Comparison results indicate that the buffer is able to significantly reduce the SU blocking probability and non-completion probability with very minor increased forced termination probability. The analytic model has been verified by extensive simulation.
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paper_title: Hidden Markov process based dynamic spectrum access for cognitive radio

paper_content:

Cognitive radio is an emerging technology for sensing and dynamic access of spectrum in mobile radio environments. It aims at dynamically allocating unused bandwidth among secondary users without causing harmful interference to the primary users. This approach, which has clear economical benefits, has recently attracted significant research effort. In this paper, we propose a new approach to dynamic spectrum access in which the occupancy state of each frequency band at each time instant is estimated, and available bands are allocated accordingly. Estimation is performed from power spectral density measurements which are assumed to obey a hidden Markov process. The value of the hidden state represents the status of a given frequency band which could be free or occupied. We have trained the system using real spectrum measurements, and tested it on simulated data for which the occupancy state of each frequency band at each time instant is known. We demonstrate the performance of the proposed approach and compare it with a simple energy detector which has previously been proposed for this application.1
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paper_title: Stackelberg game for utility-based cooperative cognitiveradio networks

paper_content:

With the development of cognitive radio technologies, dynamic spectrum access becomes a promising approach to increase the efficiency of spectrum utilization and solve spectrum scarcity problem. Under dynamic spectrum access, unlicensed wireless users (secondary users) can dynamically access the licensed bands from legacy spectrum holders (primary users) on an opportunistic basis. While most primary users in existing works assume secondary transmissions as negative interference and don't actively involve them into the primary transmission, in this paper, motivated by the idea of cooperative communication, we propose a cooperative cognitive radio framework, where primary users, aware of the existence of secondary users, may select some of them to be the cooperative relay, and in return lease portion of the channel access time to them for their own data transmission. Secondary users cooperating with primary transmissions have the right to decide their payment made for primary user in order to achieve a proportional access time to the wireless media. Both primary and secondary users target at maximizing their utilities in terms of their transmission rate and revenue/payment. This model is formulated as a Stackelberg game and a unique Nash Equilibrium point is achieved in analytical format. Based on the analysis we discuss the condition under which cooperation will increase the performance of the whole system. Both analytical result and numerical result show that the cooperative cognitive radio framework is a promising framework under which the utility of both primary and secondary system are maximized.
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paper_title: Cognitive Radio Resource Management Using Multi-Agent Systems

paper_content:

This paper investigates cooperative radio resource management for multiple cognitive radio networks in interference environments. The objective of this research is to manage shared radio resources fairly among multiple non- cooperative cognitive radio networks to optimize the overall performance. We emphasize the underlying predictability of network conditions and promote management solutions tailored to different interference environments. A multi-agent-system- based approach is proposed to achieve information sharing and decision distribution among multiple cognitive radio networks in a distributed manner. We address the distributed constraint optimization problem (DCOP) in cognitive radio networks and study the effectiveness of DCOP algorithms to find the optimal radio resource assignment through communications between distributed agents.
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paper_title: Dynamic spectrum allocation in cognitive radio using hidden Markov models: Poisson distributed case

paper_content:

Cognitive radio networks can be designed to manage the radio spectrum more efficiently by utilizing the spectrum holes in primary users' licensed frequency bands. Recent studies have shown that the radio spectrum is poorly utilized by the licensed users even in urban geographical areas. This spectrum utilization can be improved significantly by making it possible for secondary users (who are not being served by the primary system) to access spectrum holes, i.e., frequency bands not used by licensed users. In this novel work, we use hidden Markov models (HMMs) to model and predict the spectrum occupancy of licensed radio bands. The proposed technique can dynamically select different licensed bands for its own use with significantly less interference from and to the licensed users. It is found that by predicting the duration of spectrum holes of primary users, the CR can utilize them more efficiently by leaving the band, that it currently occupies, before the start of traffic from the primary user of that band. We propose a simple algorithm, called the Markov-based channel prediction algorithm (MCPA), for dynamic spectrum allocation in cognitive radio networks. In this work, we present the performance of our proposed dynamic spectrum allocation algorithm when the channel state occupancy of primary users are assumed to be Poisson distributed. The impact of CR transmission on the licensed users is also presented. It is shown that significant SIR improvements can be achieved using HMM based dynamic spectrum allocation as compared to the traditional CSMA based approach. The results obtained using HMM are very promising and HMM can offer a new paradigm for predicting channel behavior in cognitive radio, an area that has been of much research interest lately.
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paper_title: Decentralized cognitive MAC for opportunistic spectrum access in ad hoc networks: A POMDP framework

paper_content:

We propose decentralized cognitive MAC protocols that allow secondary users to independently search for spectrum opportunities without a central coordinator or a dedicated communication channel. Recognizing hardware and energy constraints, we assume that a secondary user may not be able to perform full-spectrum sensing or may not be willing to monitor the spectrum when it has no data to transmit. We develop an analytical framework for opportunistic spectrum access based on the theory of partially observable Markov decision process (POMDP). This decision-theoretic approach integrates the design of spectrum access protocols at the MAC layer with spectrum sensing at the physical layer and traffic statistics determined by the application layer of the primary network. It also allows easy incorporation of spectrum sensing error and constraint on the probability of colliding with the primary users. Under this POMDP framework, we propose cognitive MAC protocols that optimize the performance of secondary users while limiting the interference perceived by primary users. A suboptimal strategy with reduced complexity yet comparable performance is developed. Without additional control message exchange between the secondary transmitter and receiver, the proposed decentralized protocols ensure synchronous hopping in the spectrum between the transmitter and the receiver in the presence of collisions and spectrum sensing errors
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paper_title: Multiagent Based Spectrum Sharing Using Petri Nets

paper_content:

This paper presents a cooperative framework for dynamic spectrum access in cognitive radio networks, where the cognitive radio devices may use the currently unutilized spectrum dynamically and opportunistically. The proposed solution works on the principle of multiagent system that allows the cooperation amongst several participating devices. The key aspect of our design is the deployment of agents on each of the primary and cognitive radio device that cooperates in order to have a better and dynamic use of the spectrum. For cooperation, contract net protocol is considered allowing spectrum to be dynamically allocated by having a series of exchange of messages. Due to the concurrent, distributed and autonomous nature of our approach, Petri nets are adopted to model the behavior of cooperative framework. Based on Petri nets, we study the internal message passing and spectrum allocation mechanism between the participating primary and cognitive radio users and identify the information needed by the agents to make cooperative decisions. Then, using empirical results, we show that our approach achieves up to 80% of the whole utility within the span of few messages, and provides an effective mechanism for distributed spectrum allocation.
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paper_title: Analysis of Cognitive Radio Spectrum Access with Optimal Channel Reservation

paper_content:

A Markov chain analysis for spectrum access in licensed bands for cognitive radios is presented and forced termination probability, blocking probability and traffic throughput are derived. In addition, a channel reservation scheme for cognitive radio spectrum handoff is proposed. This scheme allows the tradeoff between forced termination and blocking according to QoS requirements. Numerical results show that the proposed scheme can greatly reduce forced termination probability at a slight increase in blocking probability
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paper_title: Opportunistic Spectrum Access in Cognitive Radio Networks: A Queueing Analytic Model and Admission Controller Design

paper_content:

Cognitive radio (CR) technology is an innovative radio design philosophy in order to increase the spectrum utilization by exploiting the unused spectrum in dynamically changing environments. Specifically, the CR technology will allow a group of potential users (referred to as secondary users) to access available spectrum resources unused by primary users (PUs) for whom the band has been licensed. The spectrum available for secondary users (SUs) depends on PUs' activity in the licensed spectrum. In this paper, we develop a queuing analytic framework to study important performance measures experienced by SUs in a CR network. We study queuing delay and buffer statistics of SUs' packets by modeling PUs' activity as a two state Markov chain and SUs' channel quality variation as a finite state Markov chain (FSMC). In order to allocate available channels among the SUs, an opportunistic channel allocation scheme is considered. The proposed framework facilitates to design an admission controller for SUs' network in order to maintain a given quality service (QoS) requirement which is specified in the form of statistical delay guarantee.
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paper_title: Achieving Context Awareness and Intelligence in Distributed Cognitive Radio Networks: A Payoff Propagation Approach

paper_content:

Cognitive Radio (CR) is a next-generation wireless communication system that exploits underutilized licensed spectrum to optimize the utilization of the overall radio spectrum. A Distributed Cognitive Radio Network (DCRN) is a distributed wireless network established by a number of CR hosts in the absence of fixed network infrastructure. Context awareness and intelligence are key characteristics of CR networks that enable the CR hosts to be aware of their operating environment in order to make an optimal joint action. This research aims to achieve context awareness and intelligence in DCRN using our novel Locally-Confined Payoff Propagation (LCPP), which is an important feature in Multi-Agent Reinforcement Learning (MARL). The LCPP mechanism is suitable to be applied in most applications in DCRN that require context awareness and intelligence such as scheduling, congestion control, as well as Dynamic Channel Selection (DCS), which is the focus of this paper. Simulation results show that the LCPP mechanism is a promising approach. The LCPP mechanism converges to an optimal joint action including networks with cyclic topology. Fast convergence is possible. The investigation in this paper serve as an important foundation for future work in this research field.
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paper_title: Resource Pricing with Primary Service Guarantees in Cognitive Radio Networks: A Stackelberg Game Approach

paper_content:

Cognitive Radio (CR) is envisioned as one of the most promising technologies to solve the problem of spectrum scarcity. A critical problem that limits the development of CR technology is the absence of a mechanism efficient enough to allocate under-utilized spectrum resource from primary users (PUs) to multiple secondary users (SUs) [1], [2]. Toward this end, we adopt "Game Theory" [3], [4] as our modeling tool. Spectrum users can be modeled as selfish, rational players in this spectrum selling game with PUs as spectrum sellers and SUs as buyers. Considering that PUs always know more about the "market" than SUs and marking prices should always be ahead of purchasing, we use a Stackelberg Game to analyze the pricing and allocation process of PUs and SUs under the circumstance of information asymmetry. A parameter I is later introduced to measure the negative impact from SUs to PUs. If given a predefined value of I, a feasible pricing region can be found to guarantee the primary service. Finally, a contract between PUs and SUs is proposed as a counterpart of the information asymmetry and a utility increase of SUs is observed when the contract is valid.
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paper_title: Competitive Pricing for Spectrum Sharing in Cognitive Radio Networks: Dynamic Game, Inefficiency of Nash Equilibrium, and Collusion

paper_content:

We address the problem of spectrum pricing in a cognitive radio network where multiple primary service providers compete with each other to offer spectrum access opportunities to the secondary users. By using an equilibrium pricing scheme, each of the primary service providers aims to maximize its profit under quality of service (QoS) constraint for primary users. We formulate this situation as an oligopoly market consisting of a few firms and a consumer. The QoS degradation of the primary services is considered as the cost in offering spectrum access to the secondary users. For the secondary users, we adopt a utility function to obtain the demand function. With a Bertrand game model, we analyze the impacts of several system parameters such as spectrum substitutability and channel quality on the Nash equilibrium (i.e., equilibrium pricing adopted by the primary services). We present distributed algorithms to obtain the solution for this dynamic game. The stability of the proposed dynamic game algorithms in terms of convergence to the Nash equilibrium is studied. However, the Nash equilibrium is not efficient in the sense that the total profit of the primary service providers is not maximized. An optimal solution to gain the highest total profit can be obtained. A collusion can be established among the primary services so that they gain higher profit than that for the Nash equilibrium. However, since one or more of the primary service providers may deviate from the optimal solution, a punishment mechanism may be applied to the deviating primary service provider. A repeated game among primary service providers is formulated to show that the collusion can be maintained if all of the primary service providers are aware of this punishment mechanism, and therefore, properly weight their profits to be obtained in the future.
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paper_title: COGNITIVE RADIO AND GAME THEORY : OVERVIEW AND SIMULATION

paper_content:

This thesis aims to clearly describe the cognitive radio and its components and operations. Moreover, it aims on describing the expected outcome from the most common techniques that are proposed for use in cognitive radios. In addition, it describes the basic principles of game theory and some simple game models that can be used to analyze the efficiency of the optimization algorithms. Furthermore, it investigates the use of load balancing algorithm and genetic algorithm in optimizing the decision making operation in cognitive radios. Matlab software simulations were carried out and the results show the promising benefit of using those two algorithms along with game theory in optimizing the dynamic spectrum allocation process.
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paper_title: Game theory for cognitive radio networks : An overview

paper_content:

Cognitive radio technology, a revolutionary communication paradigm that can utilize the existing wireless spectrum resources more efficiently, has been receiving a growing attention in recent years. As network users need to adapt their operating parameters to the dynamic environment, who may pursue different goals, traditional spectrum sharing approaches based on a fully cooperative, static, and centralized network environment are no longer applicable. Instead, game theory has been recognized as an important tool in studying, modeling, and analyzing the cognitive interaction process. In this tutorial survey, we introduce the most fundamental concepts of game theory, and explain in detail how these concepts can be leveraged in designing spectrum sharing protocols, with an emphasis on state-of-the-art research contributions in cognitive radio networking. Research challenges and future directions in game theoretic modeling approaches are also outlined. This tutorial survey provides a comprehensive treatment of game theory with important applications in cognitive radio networks, and will aid the design of efficient, self-enforcing, and distributed spectrum sharing schemes in future wireless networks.
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paper_title: Multi-agent Q-Learning of Channel Selection in Multi-user Cognitive Radio Systems: A Two by Two Case

paper_content:

Resource allocation is an important issue in cognitive radio systems. It can be done by carrying out negotiation among secondary users. However, significant overhead may be incurred by the negotiation since the negotiation needs to be done frequently due to the rapid change of primary users' activity. In this paper, a channel selection scheme without negotiation is considered for multi-user and multi-channel cognitive radio systems. To avoid collision incurred by non-coordination, each secondary user learns how to select channels according to its experience. Multi-agent reinforcement leaning (MARL) is applied in the framework of Q-learning by considering opponent secondary users as a part of the environment. The dynamics of the Q-learning are illustrated using Metrick-Polak plot. A rigorous proof of the convergence of Q-learning is provided via the similarity between the Q-learning and Robinson-Monro algorithm, as well as the analysis of convergence of the corresponding ordinary differential equation (via Lyapunov function). Examples are illustrated and the performance of learning is evaluated by numerical simulations.
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paper_title: Self-Organize Network Architecture for Multi-agent Cognitive Radio Systems

paper_content:

this paper presents self-organize network architecture for cognitive radio (CR). In order to increase the flexibility of CR, a division method and corresponding network keeping strategy is proposed in this paper, whose key part is finding the cutting edge in the interface graph. The TFCE (Tarjan-find-cutting-edge) algorithm is also given to find the cutting edge. On the basis of the division method a spectrum allocation model is introduced to research the effectiveness of the method for CR. The result shows the self-organize method could effectively add group's flexibility without affecting spectrum allocation utility or increasing system traffic.
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paper_title: Competitive Spectrum Trading in Dynamic Spectrum Access Markets: A Price War

paper_content:

The concept of dynamic spectrum access (DSA) enables the licensed spectrum to be traded in an open market where the unlicensed users can freely buy and use the available licensed spectrum bands. However, like in the other traditional commodity markets, spectrum trading is inevitably accompanied by various competitions and challenges. In this paper, we study an important business competition activity - price war in the DSA market. A non-cooperative pricing game is formulated to model the contention among multiple wireless spectrum providers for higher market share and revenues. We calculate the Pareto optimal pricing strategies for all providers and analyze the motivations behind the price war. The potential responses to the price war are in-depth discussed. Numerical results demonstrate the efficiency of the Pareto optimal strategy for the game and the impact of the price war to all participants.
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paper_title: Dynamic Spectrum Access and Management in Cognitive Radio Networks

paper_content:

Are you involved in designing the next generation of wireless networks? With spectrum becoming an ever scarcer resource, it is critical that new systems utilize all available frequency bands as efficiently as possible. The revolutionary technology presented in this book will be at the cutting edge of future wireless communications. Dynamic Spectrum Access and Management in Cognitive Radio Networks provides you with an all-inclusive introduction to this emerging technology, outlining the fundamentals of cognitive radio-based wireless communication and networking, spectrum sharing models, and the requirements for dynamic spectrum access. In addition to the different techniques and their applications in designing dynamic spectrum access methods, you'll also find state-of-the-art dynamic spectrum access schemes, including classifications of the different schemes and the technical details of each scheme. This is a perfect introduction for graduate students and researchers, as well as a useful self-study guide for practitioners.
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paper_title: COMAS: a cooperative multiagent architecture for spectrum sharing

paper_content:

Static spectrum allocation is a major problem in recent wireless network domains. Generally, these allocations lead to inefficient usage creating empty spectrum holes or white spaces. Thus, some alternatives must be ensured in order to mitigate the current spectrum scarcity. An effective technology to ensure dynamic spectrum usage is cognitive radio, which seeks the unutilized spectrum portions opportunistically and shares them with the neighboring devices. However, since users generally have a limited knowledge about their environment, we claim that cooperative behavior can provide them with the necessary information to solve the global issues. Therefore, in this paper, we develop a novel approach for spectrum allocation using a multiagent system that enables cognitive radio devices to work cooperatively with their neighboring licensed (or primary user) devices in order to utilize the available spectrum dynamically. The fundamental aspect of our approach is the deployment of an agent on each device which cooperates with its neighboring agents in order to have a better spectrum sharing. Considering the concurrent, distributed, and autonomous nature of the proposed approach, Petri nets are adopted to model the cooperative behaviors of primary and cognitive radio users. Our simulation results show that the proposed solution achieves good performance in terms of spectrum access, sustaining lower communication overhead.
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paper_title: A Cooperative Multiagent Based Spectrum Sharing

paper_content:

A major issue in recent wireless networks is the static utilization and allocation of the available spectrum. An effective solution to this problem is to detect the empty spectrum portions using cognitive radio devices and to share them with the neighboring users, in a dynamic and distributed manner. However, since nodes generally have limited knowledge about their environment, we suggest that cooperative behavior can provide them with the necessary information in order to solve the global issues. To this extend, we develop a novel approach for spectrum allocation using multiagent system cooperation that enables cognitive radio (or secondary user) devices to utilize the amount of available spectrum, dynamically and opportunistically. The key aspect of our design is the deployment of agents on each of the primary and secondary user devices that cooperate in order to have a better use of the spectrum. For cooperation, contract net protocol is considered, allowing spectrum to be dynamically allocated by having a series of exchange of messages amongst the devices. Simulation results show that our approach achieves up to 80% of the whole utility within the span of few messages, and provides an effective mechanism for distributed spectrum allocation.
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paper_title: Spectrum auction framework for access allocation in cognitive radio networks

paper_content:

In cognitive radio networks, there are two categories of networks on different channels: primary networks, which have high-priority access, and secondary networks, which have low-priority access. We develop an auction-based framework that allows networks to bid for primary and secondary access based on their utilities and traffic demands. The bids are used to solve the access allocation problem, which is that of selecting the primary and secondary networks on each channel either to maximize the auctioneer's revenue or to maximize the social welfare of the bidding networks, while enforcing incentive compatibility. We first consider the case when the bids of a network depend on which other networks it will share channels with. When there is only one secondary network on each channel, we design an optimal polynomial-time algorithm for the access allocation problem based on reduction to a maximum matching problem in weighted graphs. When there can be two or more secondary networks on a channel, we show that the optimal access allocation problem is NP-complete. Next, we consider the case when the bids of a network are independent of which other networks it will share channels with. We design a polynomial-time dynamic programming algorithm to optimally solve the access allocation problem when the number of possible cardinalities of the set of secondary networks on a channel is upper-bounded. Finally, we design a polynomial-time algorithm that approximates the access allocation problem within a factor of 2 when the above upper bound does not exist.
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paper_title: A Roadmap of Agent Research and Development

paper_content:

This paper provides an overview of research and development activities in the field of autonomous agents and multi-agent systems. It aims to identify key concepts and applications, and to indicate how they relate to one-another. Some historical context to the field of agent-based computing is given, and contemporary research directions are presented. Finally, a range of open issues and future challenges are highlighted.
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paper_title: Spectrum Management of Cognitive Radio Using Multi-agent Reinforcement Learning

paper_content:

Wireless cognitive radio (CR) is a newly emerging paradigm that attempts to opportunistically transmit in licensed frequencies, without affecting the pre-assigned users of these bands. To enable this functionality, such a radio must predict its operational parameters, such as transmit power and spectrum. These tasks, collectively called spectrum management, is difficult to achieve in a dynamic distributed environment, in which CR users may only take local decisions, and react to the environmental changes. In this paper, we introduce a multi-agent reinforcement learning approach based spectrum management. Our approach uses value functions to evaluate the desirability of choosing different transmission parameters, and enables efficient assignment of spectrums and transmit powers by maximizing long-term reward. We then investigate various real-world scenarios, and compare the communication performance using different sets of learning parameters. We also apply Kanerva-based function approximation to improve our approach's ability to handle large cognitive radio networks and evaluate its effect on communication performance. We conclude that our reinforcement learning based spectrum management can significantly reduce the interference to the licensed users, while maintaining a high probability of successful transmissions in a cognitive radio ad hoc network.
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paper_title: The Water-Filling Game in Fading Multiple-Access Channels

paper_content:

A game-theoretic framework is developed to design and analyze the resource allocation algorithms in fading multiple-access channels (MACs), where the users are assumed to be selfish, rational, and limited by average power constraints. The maximum sum-rate point on the boundary of the MAC capacity region is shown to be the unique Nash equilibrium of the corresponding water-filling game. This result sheds a new light on the opportunistic communication principle. The base station is then introduced as a player interested in maximizing a weighted sum of the individual rates. A Stackelberg formulation is proposed in which the base station is the designated game leader. In this setup, the base station announces first its strategy defined as the decoding order of the different users, in the successive cancellation receiver, as a function of the channel state. In the second stage, the users compete conditioned on this particular decoding strategy. This formulation is shown to be able to achieve all the corner points of the capacity region, in addition to the maximum sum-rate point. On the negative side, it is shown that there does not exist a base station strategy in this formulation that achieves the rest of the boundary points. To overcome this limitation, a repeated game approach, which achieves the capacity region of the fading MAC, is presented. Finally, the study is extended to vector channels highlighting interesting differences between this scenario and the scalar channel case.
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paper_title: Cognitive Radio Channel Allocation Using Auction Mechanisms

paper_content:

We adopt the auction mechanisms into the dynamic channel allocation of cognitive radio networks. Under auction schemes, users bid the transmission time slots to gain access to the licensed channel. Their bids accumulate throughout the repeated bidding process over time, and they pay the "bill" at the end of the time frame in the form of out-band sensing. By doing so, we allocate the channel to the user who values it most, and impose a responsibility for out-band sensing which is split up among users according to their aggregate winning bids. We study the allocation under both first and second price sealed-bid auctions and find that they yield similar outcomes in terms of throughput and efficiency. We also develop two auction-based improvement schemes to address the traffic issue in secondary nodes, and the system performance receives a significant boost as a result.
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paper_title: Dynamic Spectrum Sharing in Cognitive Radio Networks: a Solution based on Multiagent Systems

paper_content:

In modern day wireless networks, spectrum utilization and allocation are static. Generally, static spectrum allocation is not a feasible solution considering the distributed and dynamic nature of wireless devices, thus some alternatives must be ensured in order to allocate spectrum dynamically and to mitigate the current spectrum scarcity. An effective technology to ensure dynamic spectrum usage is cognitive radio, which seeks the unutilized spectrum holes opportunistically and shares them with the neighboring devices. Using cognitive radio capabilities, the nodes are not restrained to static spectrum utilization, rather they can choose it on demand. However, dynamic spectrum usage raises several challenges, which need to be addressed in detail. These challenges include efficient allocation of spectrum between licensed (or primary) and cognitive radio (or secondary) users in order to maximize spectrum utilization and to avoid device level interferences. To this extend, we develop a novel solution for spectrum allocation using multiagent system cooperation that enables secondary user devices to utilize the amount of available spectrum, dynamically and cooperatively. The key aspect of our design is the deployment of agents on each of the primary and secondary user devices that cooperate in order to have a better use of the spectrum. For cooperation, contract net protocol is used, allowing spectrum to be dynamically allocated by having a series of message exchanges amongst the devices. Simulation results show that our solution achieves up to 80% of the whole utility within the span of few messages, and provides an effective mechanism for dynamic spectrum allocation.
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paper_title: ON USING MULTI AGENT SYSTEMS IN COGNITIVE RADIO NETWORKS : A SURVEY

paper_content:

In the last decade, cognitive radio technology received a lot of consideration for spectrum optimization. This issue creates huge opportunities for interesting research and development in a wide range of applications. This paper presents a state of the art on cognitive radio researches especially works using multi-agent systems. We propose among others a classification of cognitive radio proposals based on multi-agent concept and point out the pros and cons for each of the described approach.
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paper_title: A continuous time Markov model for unlicensed spectrum access

paper_content:

Recent static spectrum allocations have created an opportunity to develop novel solutions that can efficiently share the available spectrum both in licensed and unlicensed bands. Considering the relative rarity of solutions for unlicensed spectrum access, in this paper, we propose a scheme, where the cognitive radio (CR) devices (equipped with agents) interact with their neighbors to form several coalitions over the unlicensed bands. These types of coalitions can provide a less-conflicted spectrum access as the agents mutually agree for spectrum sharing. Further, we present a continuous time Markov chain (CTMC) with queuing to model the user interactions with the movement of spectrum access process from one state to another and derive the important performance metric as the blocking probability. Numerical results are presented to observe the impact of forming multiple coalitions on the blocking probability.
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paper_title: Mobile Flexible Networks: The challenges ahead

paper_content:

The general framework of mobile flexible networks is to design self-organizing secure networks where terminals and base stations interact and self-adapt in an intelligent manner without the need of a central controller (or with the right amount of regulation...just enough to let the agents in the network exploit fully the degrees of freedom). Of course, the design depends on the mobility pattern and delay tolerance as in highly mobile environments, exchange of control signaling bears a huge cost whereas for fixed (non-mobile) networks, the designer can dedicate a fraction of the rate (which is negligible in terms of overhead) to optimize the system. One of the big challenges is to find how to optimally split the intelligence between cognitive terminals and cognitive networks. In this paper, we discuss the challenges ahead and provide some research directions to develop the theoretical foundations of these networks.
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paper_title: A user assistant for QoS negotiation in a dynamic environment using agent technology

paper_content:

This paper presents an assistant to help the user in negotiating the desired quality of service in a dynamic environment using the agent technology. A multi-agent system is proposed in order to solve problems and accomplish tasks in a distributed and autonomous way. This user assistant negotiates dynamically the QoS (quality of service) on the user's behalf, follows the user's behavior to be able to predict his future location in wireless networks, anticipate the negotiation and manage the re-negotiation. The negotiation can take place in two different manners, using agents that will reach an agreement with the best provider or using a dynamic negotiation protocol called SLN NSLP.
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paper_title: Routing in Distributed Cognitive Radio Networks: A Survey

paper_content:

Cognitive Radio Networks (CRNs) have been receiving significant research attention recently due to their ability to solve issues associated with spectrum congestion and underutilization. In a CRN, unlicensed users (or Secondary Users, SUs) are able to exploit and use underutilized licensed channels, but they must evacuate the channels if any interference is caused to the licensed users (or Primary Users, PUs) who own the channels. Due to the dynamicity of spectrum availability in CRNs, design of protocols and schemes at different layers of the SU's network stack has been challenging. In this article, we focus on routing and discuss the challenges and characteristics associated with it. Subsequently, we provide an extensive survey on existing routing schemes in CRNs. Generally speaking, there are three categories of challenges, namely channel-based, host-based, and network-based. The channel-based challenges are associated with the operating environment, the host-based with the SUs, and the network-based with the network-wide SUs. Furthermore, the existing routing schemes in the literature are segregated into three broad categories based on the relationship between PUs and SUs in their investigation, namely intra-system, inter-system, and hybrid-system; and within each category, they are further categorized based on their types, namely Proactive, Reactive, Hybrid, and Adaptive Per-hop. Additionally, we present performance enhancements achieved by the existing routing schemes in CRNs. Finally, we discuss various open issues related to routing in CRNs in order to establish a foundation and to spark new interests in this research area.
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paper_title: Routing in cognitive radio networks: Challenges and solutions

paper_content:

Cognitive radio networks (CRNs) are composed of cognitive, spectrum-agile devices capable of changing their configurations on the fly based on the spectral environment. This capability opens up the possibility of designing flexible and dynamic spectrum access strategies with the purpose of opportunistically reusing portions of the spectrum temporarily vacated by licensed primary users. On the other hand, the flexibility in the spectrum access phase comes with an increased complexity in the design of communication protocols at different layers. This work focuses on the problem of designing effective routing solutions for multi-hop CRNs, which is a focal issue to fully unleash the potentials of the cognitive networking paradigm. We provide an extensive overview of the research in the field of routing for CRNs, clearly differentiating two main categories: approaches based on a full spectrum knowledge, and approaches that consider only local spectrum knowledge obtained via distributed procedures and protocols. In each category we describe and comment on proposed design methodologies, routing metrics and practical implementation issues. Finally, possible future research directions are also proposed.
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paper_title: Improving video conferencing application quality for a mobile terminal through cognitive radio

paper_content:

Cognitive radio (CR) is a form of wireless communication in which a transceiver can intelligently detect which communication channels are in use and which are not, and instantly move into vacant channels while avoiding occupied ones. This optimizes the use of available radio-frequency (RF) spectrum while minimizing interference to other users. In this paper, we propose a new approach which uses the CR for improving video conferencing application quality for a cognitive radio mobile terminal (CRMT). We also show through experimentation the interest of our approach.
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paper_title: Auction-Based Agent Negotiation in Cognitive Radio Ad Hoc Networks

paper_content:

The explosive growth of wireless services in recent years illustrates the growing demand for communications, so the spectrum becomes more congested. We know that static spectrum allocation is a major problem in wireless networks. Generally, these allocations lead to an inefficient use of spectrum. To solve the problem of congestion, cognitive radio networks use dynamic spectrum access. In this paper, we use a technique based on auctions theory known for its simplicity and facilitates the allocation of scarce resources.
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paper_title: Transport Layer Protocols for Cognitive Networks

paper_content:

The cognitive radio networks or CogNets poses several new challenges to the transport layer protocols, because of many unique features of cognitive radio based devices used to build them. CogNets not only have inherited all features of wireless networks, but also their link connections are intermittent and discontinuous. Exiting transport layer protocols are too slow to respond quickly for utilizing available link capacity. Furthermore, existing self-timed transport layer protocols are neither designed for nor able to provide efficient reliable end-to-end transport service in CogNets, where wide round trip delay variations naturally occur. We identify (i) requirements of protocols for the transport layer of CogNets, (ii) propose a generic architecture for implementing a family of protocols that fulfill desired requirements, (iii) design, implement, and evaluate a family of best-effort transport protocols for serving delay-tolerant applications. Results obtained from ns-2 network simulator show that the proposed protocols have potential for significantly improving end-to-end throughput. For instance, at 1% and 5% packet loss rates one of the proposed protocol has shown about 21% and 95% increase in end-to-end throughput for file transfer application.
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paper_title: TP-CRAHN: a Transport Protocol for Cognitive Radio Ad-Hoc Networks

paper_content:

Existing research in transport protocols for wireless ad-hoc networks has focused on reliable end-to-end packet delivery under uncertain channel conditions, route failures due to node mobility and link congestion. In a cognitive radio (CR) environment, there are several key challenges that must be addressed apart from the above concerns. The intermittent spectrum sensing undertaken by the CR users, the activity of the licensed users of the spectrum, large-scale bandwidth variation based on spectrum availability, and the channel switching process need to be considered in the transport protocol design. In this paper, a window-based Transport Protocol for CR Ad-Hoc Networks, TP-CRAHN, is proposed that distinguishes each of these events by a combination of explicit feedback from the intermediate nodes and the destination. This is achieved by adapting the classical TCP rate control algorithm running at the source to closely interact with the physical layer channel information, the link layer functions of spectrum sensing and buffer management, and a predictive mobility framework that is developed at the network layer. To the best of our knowledge, this is the first work on the transport layer to specifically address the concerns of the CR ad-hoc networks and our approach is thoroughly validated by simulation experiments.
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Title: A Survey on Dynamic Spectrum Access Techniques in Cognitive Radio Networks

Section 1: Introduction
Description 1: This section should provide an overview of cognitive radio networks, the need for dynamic spectrum access (DSA), and the research progress and challenges in this domain.

Section 2: Cognitive Radio
Description 2: This section should define cognitive radio, its history, and its primary functions including spectrum sensing, spectrum decision, spectrum sharing, and spectrum mobility. 

Section 3: Spectrum Sensing
Description 3: This section should explain the basic functionality of spectrum sensing in cognitive radio, including methods for detecting unused spectrum and challenges like measuring interference at the receiver.

Section 4: Spectrum Decision
Description 4: This section should detail the decision models required for spectrum access, including the complexity involved and the tools like stochastic optimization to achieve efficient spectrum access.

Section 5: Spectrum Analysis or Sharing
Description 5: This section should discuss how the results from spectrum sensing are analyzed to estimate spectrum quality for access by secondary users.

Section 6: Spectrum Mobility or Handoff
Description 6: This section should describe the process and importance of spectrum mobility which allows cognitive radio users to change frequency for effective communication.

Section 7: Dynamic Spectrum Access
Description 7: This section should provide an overview of dynamic spectrum access, its necessity due to growing spectrum congestion, and its implementation principles.

Section 8: Spectrum Access using Auctions
Description 8: This section should describe auction-based methods for spectrum access, including various auction types and their impact on spectrum management.

Section 9: Spectrum Access using Game Theory
Description 9: This section should explain game theory approaches for spectrum access in cognitive radio networks, highlighting cooperative and competitive games and concepts like Nash Equilibrium.

Section 10: Spectrum Access using Markov Approaches
Description 10: This section should provide insight into the use of Markov models to analyze and predict spectrum access and channel behavior in cognitive radio networks.

Section 11: Spectrum Access using Multi Agent Systems
Description 11: This section should explore the use of multi-agent systems for distributed spectrum management in cognitive radio networks, including agent-based cooperation and negotiation methods.

Section 12: Conclusion
Description 12: This section should summarize the survey, highlighting the complementary nature of the different DSA techniques and future research directions such as integration of multi-agent systems.