COGNITIVE RADIOS FOR DYNAMIC SPECTRUM ACCESS - Dynamic Spectrum Sharing: A Game Theoretical Overview
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paper_title: Fair multiuser channel allocation for OFDMA networks using Nash bargaining solutions and coalitions

paper_content:

In this paper, a fair scheme to allocate subcarrier, rate, and power for multiuser orthogonal frequency-division multiple-access systems is proposed. The problem is to maximize the overall system rate, under each user's maximal power and minimal rate constraints, while considering the fairness among users. The approach considers a new fairness criterion, which is a generalized proportional fairness based on Nash bargaining solutions and coalitions. First, a two-user algorithm is developed to bargain subcarrier usage between two users. Then a multiuser bargaining algorithm is developed based on optimal coalition pairs among users. The simulation results show that the proposed algorithms not only provide fair resource allocation among users, but also have a comparable overall system rate with the scheme maximizing the total rate without considering fairness. They also have much higher rates than that of the scheme with max-min fairness. Moreover, the proposed iterative fast implementation has the complexity for each iteration of only O(K/sup 2/Nlog/sub 2/N+K/sup 4/), where N is the number of subcarriers and K is the number of users.
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paper_title: Belief-Assisted Pricing for Dynamic Spectrum Allocation in Wireless Networks with Selfish Users

paper_content:

In order to fully utilize the scarce spectrum resources, with the development of cognitive radio technologies, dynamic spectrum allocation becomes a promising approach to increase the efficiency of spectrum usage. In this paper, we consider the spectrum allocation in wireless networks with multiple selfish legacy spectrum holders and unlicensed users as multi-stage dynamic games. A belief-assisted dynamic pricing approach is proposed to optimize overall spectrum efficiency while keeping the participating incentives of the users based on double auction rules. Moreover, considering the budget constraints of the unlicensed users, a dynamic programming approach is further developed to optimize the spectrum allocation over time. The simulation results show that our proposed scheme not only approaches optimal outcomes with low overhead compared to general continuous double auction mechanisms, but also fully exploits the time diversity of spectrum resources when budget constraints exist
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paper_title: Spectrum sharing for unlicensed bands

paper_content:

We study a spectrum sharing problem in an unlicensed band where multiple systems coexist and interfere with each other. We first analyze a cooperative setting where all the systems collaborate to achieve a common goal. Under the assumptions that the systems communicate with Gaussian signals and treat interference as noise, we study the structure of the optimal power allocations. We show that any Pareto efficient vector of rates can be achieved with piece-wise constant power allocations. Moreover, if a strong interference condition among all the systems is satisfied, we show that frequency division multiplexing is optimal. We then consider a non-cooperative situation, where the systems act in a selfish and rational way, and investigate how the lack of cooperation can affect performance. Using game theory, we first analyze the possible outcomes of a one shot game, and observe that in many cases an inefficient solution results. We show that by extending the game definition to that of a repeated game, the possibility of building reputations and applying punishments allows to enlarge the set of achievable rates. We present examples that show that in many cases, the performance loss due to lack of cooperation is small. We also provide a converse theorem that proves that our results are tight and quantify the best achievable performance in a non-cooperative scenario
---
paper_title: Distributed spectrum allocation via local bargaining

paper_content:

In this paper, we present an adaptive and distributed approach to spectrum allocation in mobile ad-hoc networks. We propose a local bargaining approach where users affected by the mobility event self-organize into bargaining groups and adapt their spectrum assignment to approximate a new optimal assignment. The number of computations required to adapt to topology changes can be significantly reduced compared to that of the conventional topology-based optimizations that ignore the prior assignment. In particular, we propose a Fairness Bargaining with Feed Poverty to improve fairness in spectrum assignment and derive a theoretical lower bound on the minimum assignment each user can get from bargaining for certain network configurations. Such bound can be utilized to guide the bargaining process. We also show that the difference between the proposed bargaining approach and the true optimal approach is upper-bounded. Experimental results demonstrate that the proposed bargaining approach provides similar performance as the topology-based optimization but with more than 50% of reduction in complexity.
---
paper_title: Auction-Based Spectrum Sharing

paper_content:

We study auction mechanisms for sharing spectrum among a group of users, subject to a constraint on the interference temperature at a measurement point. The users access the channel using spread spectrum signaling and so interfere with each other. Each user receives a utility that is a function of the received signal-to-interference plus noise ratio. We propose two auction mechanisms for allocating the received power. The first is an auction in which users are charged for received SINR, which, when combined with logarithmic utilities, leads to a weighted max-min fair SINR allocation. The second is an auction in which users are charged for power, which maximizes the total utility when the bandwidth is large enough and the receivers are co-located. Both auction mechanisms are shown to be socially optimal for a limiting "large system" with co-located receivers, where bandwidth, power and the number of users are increased in fixed proportion. We also formulate an iterative and distributed bid updating algorithm, and specify conditions under which this algorithm converges globally to the Nash equilibrium of the auction.
---
paper_title: Distributed spectrum allocation via local bargaining

paper_content:

In this paper, we present an adaptive and distributed approach to spectrum allocation in mobile ad-hoc networks. We propose a local bargaining approach where users affected by the mobility event self-organize into bargaining groups and adapt their spectrum assignment to approximate a new optimal assignment. The number of computations required to adapt to topology changes can be significantly reduced compared to that of the conventional topology-based optimizations that ignore the prior assignment. In particular, we propose a Fairness Bargaining with Feed Poverty to improve fairness in spectrum assignment and derive a theoretical lower bound on the minimum assignment each user can get from bargaining for certain network configurations. Such bound can be utilized to guide the bargaining process. We also show that the difference between the proposed bargaining approach and the true optimal approach is upper-bounded. Experimental results demonstrate that the proposed bargaining approach provides similar performance as the topology-based optimization but with more than 50% of reduction in complexity.
---
paper_title: Spectrum sharing for unlicensed bands

paper_content:

We study a spectrum sharing problem in an unlicensed band where multiple systems coexist and interfere with each other. We first analyze a cooperative setting where all the systems collaborate to achieve a common goal. Under the assumptions that the systems communicate with Gaussian signals and treat interference as noise, we study the structure of the optimal power allocations. We show that any Pareto efficient vector of rates can be achieved with piece-wise constant power allocations. Moreover, if a strong interference condition among all the systems is satisfied, we show that frequency division multiplexing is optimal. We then consider a non-cooperative situation, where the systems act in a selfish and rational way, and investigate how the lack of cooperation can affect performance. Using game theory, we first analyze the possible outcomes of a one shot game, and observe that in many cases an inefficient solution results. We show that by extending the game definition to that of a repeated game, the possibility of building reputations and applying punishments allows to enlarge the set of achievable rates. We present examples that show that in many cases, the performance loss due to lack of cooperation is small. We also provide a converse theorem that proves that our results are tight and quantify the best achievable performance in a non-cooperative scenario
---
paper_title: Auction-Based Spectrum Sharing

paper_content:

We study auction mechanisms for sharing spectrum among a group of users, subject to a constraint on the interference temperature at a measurement point. The users access the channel using spread spectrum signaling and so interfere with each other. Each user receives a utility that is a function of the received signal-to-interference plus noise ratio. We propose two auction mechanisms for allocating the received power. The first is an auction in which users are charged for received SINR, which, when combined with logarithmic utilities, leads to a weighted max-min fair SINR allocation. The second is an auction in which users are charged for power, which maximizes the total utility when the bandwidth is large enough and the receivers are co-located. Both auction mechanisms are shown to be socially optimal for a limiting "large system" with co-located receivers, where bandwidth, power and the number of users are increased in fixed proportion. We also formulate an iterative and distributed bid updating algorithm, and specify conditions under which this algorithm converges globally to the Nash equilibrium of the auction.
---
paper_title: Belief-Assisted Pricing for Dynamic Spectrum Allocation in Wireless Networks with Selfish Users

paper_content:

In order to fully utilize the scarce spectrum resources, with the development of cognitive radio technologies, dynamic spectrum allocation becomes a promising approach to increase the efficiency of spectrum usage. In this paper, we consider the spectrum allocation in wireless networks with multiple selfish legacy spectrum holders and unlicensed users as multi-stage dynamic games. A belief-assisted dynamic pricing approach is proposed to optimize overall spectrum efficiency while keeping the participating incentives of the users based on double auction rules. Moreover, considering the budget constraints of the unlicensed users, a dynamic programming approach is further developed to optimize the spectrum allocation over time. The simulation results show that our proposed scheme not only approaches optimal outcomes with low overhead compared to general continuous double auction mechanisms, but also fully exploits the time diversity of spectrum resources when budget constraints exist
---
paper_title: Distributed spectrum allocation via local bargaining

paper_content:

In this paper, we present an adaptive and distributed approach to spectrum allocation in mobile ad-hoc networks. We propose a local bargaining approach where users affected by the mobility event self-organize into bargaining groups and adapt their spectrum assignment to approximate a new optimal assignment. The number of computations required to adapt to topology changes can be significantly reduced compared to that of the conventional topology-based optimizations that ignore the prior assignment. In particular, we propose a Fairness Bargaining with Feed Poverty to improve fairness in spectrum assignment and derive a theoretical lower bound on the minimum assignment each user can get from bargaining for certain network configurations. Such bound can be utilized to guide the bargaining process. We also show that the difference between the proposed bargaining approach and the true optimal approach is upper-bounded. Experimental results demonstrate that the proposed bargaining approach provides similar performance as the topology-based optimization but with more than 50% of reduction in complexity.
---
paper_title: Distributed spectrum allocation via local bargaining

paper_content:

In this paper, we present an adaptive and distributed approach to spectrum allocation in mobile ad-hoc networks. We propose a local bargaining approach where users affected by the mobility event self-organize into bargaining groups and adapt their spectrum assignment to approximate a new optimal assignment. The number of computations required to adapt to topology changes can be significantly reduced compared to that of the conventional topology-based optimizations that ignore the prior assignment. In particular, we propose a Fairness Bargaining with Feed Poverty to improve fairness in spectrum assignment and derive a theoretical lower bound on the minimum assignment each user can get from bargaining for certain network configurations. Such bound can be utilized to guide the bargaining process. We also show that the difference between the proposed bargaining approach and the true optimal approach is upper-bounded. Experimental results demonstrate that the proposed bargaining approach provides similar performance as the topology-based optimization but with more than 50% of reduction in complexity.
---
paper_title: Collusion-Resistant Dynamic Spectrum Allocation for Wireless Networks via Pricing

paper_content:

Dynamic spectrum allocation becomes a promising approach to increase the spectrum efficiency for wireless networks. However, the collusion among selfish network users may seriously deteriorate the efficiency of dynamic spectrum sharing. In this paper, we propose a collusion-resistant dynamic pricing approach to optimize overall spectrum efficiency in the scenarios of user collusion. The simulation results show that our proposed scheme achieves high efficiency of spectrum usage even with the presence of severe user collusion.
---
paper_title: Belief-Assisted Pricing for Dynamic Spectrum Allocation in Wireless Networks with Selfish Users

paper_content:

In order to fully utilize the scarce spectrum resources, with the development of cognitive radio technologies, dynamic spectrum allocation becomes a promising approach to increase the efficiency of spectrum usage. In this paper, we consider the spectrum allocation in wireless networks with multiple selfish legacy spectrum holders and unlicensed users as multi-stage dynamic games. A belief-assisted dynamic pricing approach is proposed to optimize overall spectrum efficiency while keeping the participating incentives of the users based on double auction rules. Moreover, considering the budget constraints of the unlicensed users, a dynamic programming approach is further developed to optimize the spectrum allocation over time. The simulation results show that our proposed scheme not only approaches optimal outcomes with low overhead compared to general continuous double auction mechanisms, but also fully exploits the time diversity of spectrum resources when budget constraints exist
---
paper_title: Belief-Assisted Pricing for Dynamic Spectrum Allocation in Wireless Networks with Selfish Users

paper_content:

In order to fully utilize the scarce spectrum resources, with the development of cognitive radio technologies, dynamic spectrum allocation becomes a promising approach to increase the efficiency of spectrum usage. In this paper, we consider the spectrum allocation in wireless networks with multiple selfish legacy spectrum holders and unlicensed users as multi-stage dynamic games. A belief-assisted dynamic pricing approach is proposed to optimize overall spectrum efficiency while keeping the participating incentives of the users based on double auction rules. Moreover, considering the budget constraints of the unlicensed users, a dynamic programming approach is further developed to optimize the spectrum allocation over time. The simulation results show that our proposed scheme not only approaches optimal outcomes with low overhead compared to general continuous double auction mechanisms, but also fully exploits the time diversity of spectrum resources when budget constraints exist
---

Title: COGNITIVE RADIOS FOR DYNAMIC SPECTRUM ACCESS - Dynamic Spectrum Sharing: A Game Theoretical Overview

Section 1: INTRODUCTION
Description 1: Provide an overview of the increasing demand for wireless spectrum, the inefficiencies of traditional fixed spectrum allocation, and the potential of cognitive radio technologies for dynamic spectrum access and sharing.

Section 2: ABSTRACT
Description 2: Summarize the key points regarding the use of game theoretical models for dynamic spectrum sharing and the importance of analyzing the behaviors of network users with cognitive radios.

Section 3: SYSTEM MODEL
Description 3: Explain the model for Dynamic Spectrum Access Networks (DSANs), outlining the network architecture and the role of primary and secondary users.

Section 4: COGNITIVE RADIOS FOR DYNAMIC SPECTRUM ACCESS
Description 4: Delve into the specifics of how cognitive radios enable dynamic spectrum access by secondary users and describe the main features and challenges of DSANs.

Section 5: GAME THEORETICAL MODELS FOR DYNAMIC SPECTRUM SHARING
Description 5: Introduce the motivation for applying game theory to dynamic spectrum sharing and discuss various game models that are relevant to different network scenarios.

Section 6: MOTIVATION OF GAME THEORETICAL DYNAMIC SPECTRUM SHARING
Description 6: Explore the challenges in spectrum sharing and how game theory can address issues related to the behavior and interaction of network users.

Section 7: GAME MODELS
Description 7: Describe the components of game models in spectrum sharing, such as players, strategy spaces, and payoff functions, and discuss different game scenarios including cooperative and non-cooperative models.

Section 8: EFFICIENT DISTRIBUTED DYNAMIC SPECTRUM SHARING
Description 8: Investigate distributed approaches for spectrum sharing in the absence of centralized authorities, emphasizing the importance of users' local information.

Section 9: LOCAL BARGAINING
Description 9: Detail the local bargaining strategies for spectrum assignment in changing network topologies to achieve efficient and conflict-free spectrum sharing.

Section 10: REPEATED SPECTRUM SHARING GAME MODEL
Description 10: Explain the benefits of using a repeated game model to study long-term interactions among secondary users for more efficient spectrum sharing.

Section 11: AUCTION-BASED SPECTRUM SHARING GAME
Description 11: Discuss auction-based methods for spectrum sharing between primary and secondary users, including the different payment metrics and the proposed bid-updating algorithm.

Section 12: BELIEF-ASSISTED PRICING
Description 12: Describe the belief-assisted pricing strategy for efficient distributed spectrum sharing when multiple primary and secondary users coexist.

Section 13: GAME THEORETICAL OPTIMALITY ANALYSIS
Description 13: Provide an overview of how game theory is used to analyze the optimality of dynamic spectrum sharing outcomes and the relevant theoretical criteria.

Section 14: PRICE OF ANARCHY
Description 14: Define the concept of price of anarchy and its significance in understanding non-cooperative game outcomes in the absence of centralized control.

Section 15: NBS IN SPECTRUM SHARING GAMES
Description 15: Explain the role of the Nash Bargaining Solution (NBS) in ensuring efficient and fair spectrum sharing among multiple users.

Section 16: DYNAMIC PROGRAMMING FOR DSSGS
Description 16: Discuss the application of dynamic programming to study optimal spectrum sharing considering the dynamic nature of spectrum resources.

Section 17: NUMERICAL RESULTS
Description 17: Present the numerical evaluation of the proposed belief-assisted dynamic spectrum sharing approach and dynamic programming schemes based on simulated network scenarios.

Section 18: CONCLUSIONS
Description 18: Summarize the importance of game theoretical approaches in developing efficient and fair spectrum sharing techniques for next-generation wireless networks and suggest areas for further research.