Game Theoretic Analysis of Joint Channel Selection and Power Allocation in Cognitive radio Networks

He, Hao; Chen, Jie; Deng, Shoufeng; Li, Shaoqian

doi:10.1109/crowncom.2008.4562549

Cited by 11 publications

(3 citation statements)

References 9 publications

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“…Example 3: From Theorem 7, any identical interest game is an EPG. Almost all games found in studies applying identical interest games [19], [27], [55], [74], [107], [142], [165] have the form of game G2 := (I, (A i ), (u2 i )), where…”

Section: ) Coordination-dummy Gamesmentioning

confidence: 99%

A Comprehensive Survey of Potential Game Approaches to Wireless Networks

Yamamoto

2015

IEICE Trans. Commun.

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SUMMARY Potential games form a class of non-cooperative games where the convergent of unilateral improvement dynamics is guaranteed in many practical cases. The potential game approach has been applied to a wide range of wireless network problems, particularly to a variety of channel assignment problems. In this paper, the properties of potential games are introduced, and games in wireless networks that have been proven to be potential games are comprehensively discussed. key words: potential game, game theory, radio resource management, channel assignment, transmission power control IntroductionThe broadcast nature of wireless transmissions causes cochannel interference and channel contention, which can be viewed as interactions among transceivers. Interactions among multiple decision makers can be formulated and analyzed using a branch of applied mathematics called game theory [61], [131]. Game-theoretic approaches have been applied to a wide range of wireless communication technologies, including transmission power control for code division multiple access (CDMA) cellular systems [153] and cognitive radios [132]. For a summary of game-theoretic approaches to wireless networks, we refer the interested reader to [68] [189].In this paper, we focus on potential games [126], which form a class of strategic form games with the following desirable properties:• The existence of a Nash equilibrium in potential games is guaranteed in many practical situations [126] (Theorems 1 and 2 in this paper), but is not guaranteed for general strategic form games. Example 2 in Sect. 2. We provide an overview of problems in wireless networks that can be formulated in terms of potential games. We also clarify the relations among games, and provide simpler proofs of some known results. Problem-specific learning algorithms [92], [168] are beyond the scope of this paper.The remainder of this paper is organized as follows: In Sect. 2, 3, and 4, we introduce strategic form games, potential games, and learning algorithms, respectively. We then discuss various potential games in Sects. 5 to 18, as shown in Table 1. Finally, we provide a few concluding remarks in Sect. 19.The notation used here is shown in Table 2. Unless the context indicates otherwise, sets of strategies are denoted by calligraphic uppercase letters, e.g., A i , strategies are denoted by lowercase letters, e.g., a i ∈ A i , and tuples of strategies are denoted by boldface lowercase letters, e.g., a. Note that a i is a scalar variable when A i is a set of scalars or indices, a i is a vector variable when A i is a set of vectors, and a i is a set variable when A i is a collection of sets.We use R to denote the set of real numbers, R + to denote the set of nonnegative real numbers, R ++ to denote the set of positive real numbers, and C to denote the set of complex numbers. The cardinality of set A is denoted by |A|. The power set of A is denoted by 2 A . Finally, ½condition is the indicator function, which is one when condition is true and is zero otherwise.We treat many sy...

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Section: ) Coordination-dummy Gamesmentioning

confidence: 99%

A Comprehensive Survey of Potential Game Approaches to Wireless Networks

Yamamoto

2015

IEICE Trans. Commun.

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“…There exists connection with the decision choose in adjusting the spectrum allocation. As a efficient method in helping solving decision-making problems, game theory becomes a good way in allocating spectrum in effect [3].…”

Section: Introductionmentioning

confidence: 99%

An Improved Game-theoretic Spectrum Sharing in Cognitive Radio Systems

Zhu

2011

2011 Third International Conference on Communications and Mobile Computing

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In this paper, an improved game-theoretic spectrum sharing algorithm is proposed. Besides considering the available bandwidth, a reliance factor that represents how the primary users would like to lease the free spectrum to secondary users is introduced and the battery capacity of secondary users is taken into account. The simulation results show that the shared spectrum is in direct proportion to the reliance and battery capacity. The existence and uniqueness of Nash equilibrium are proved.

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“…Without prejudice to the primary user, each secondary user can choose channels according to their quality of service (Qos) requirements and local information. A spectrum sharing method which bases on potential game theory is proposed in [4], [5]. Cognitive radio users can adaptively select a channel to minimize the interference and ultimately achieve the Nash equilibrium.…”

Section: Introductionmentioning

confidence: 99%

A New Algorithm of Spectrum Allocation for Cognitive Radio Based on Cooperative Game

Zhu

2010

2010 6th International Conference on Wireless Communications Networking and Mobile Computing (WiCOM)

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Secondary users, which base on the spectrum pricing function given by primary users, can compete the spectrum resource with each other through game theory in cognitive radio system. It can be divided into cooperative game and noncooperative game according to whether the secondary users cooperate or not in the spectrum sharing. In this paper, based on the Nash bargaining in cooperative game, an improved utility function is proposed to maximize the profit product of all the secondary users. The cooperative game algorithm of spectrum allocation in cognitive radio is found and the priority of secondary users is introduced. We prove the existence and uniqueness of NBS (Nash Bargaining Solution) for the new utility in cooperative game. The simulation results show that the new algorithm can reflect the secondary users' priorities of spectrum allocation by setting the parameters properly and make sure the spectrum allocation becomes more efficient and fair.

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Game Theoretic Analysis of Joint Channel Selection and Power Allocation in Cognitive radio Networks

Cited by 11 publications

References 9 publications

A Comprehensive Survey of Potential Game Approaches to Wireless Networks

A Comprehensive Survey of Potential Game Approaches to Wireless Networks

An Improved Game-theoretic Spectrum Sharing in Cognitive Radio Systems

A New Algorithm of Spectrum Allocation for Cognitive Radio Based on Cooperative Game

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