Joint Optimization of Transmission-Order Selection and Channel Allocation for Bidirectional Wireless Links—Part I: Game Theoretic Analysis

Uykan, Zekeriya; Jäntti, Riku

doi:10.1109/twc.2014.2314633

Cited by 9 publications

(16 citation statements)

References 26 publications

(71 reference statements)

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“…In contrast to unidirectional links assumed in the TX-RX pair model, Uykan and Jäntti [175], [176] discussed a channel assignment problem for bidirectional links and proposed a joint transmission order and channel assignment algorithm.…”

Section: Channel Assignment To Manage Received and Generated Interfermentioning

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: Channel Assignment To Manage Received and Generated Interfermentioning

confidence: 99%

A Comprehensive Survey of Potential Game Approaches to Wireless Networks

Yamamoto

2015

IEICE Trans. Commun.

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“…In Part I [54], we thoroughly analyze the TO optimization problem in the presence of the CA, i.e., the joint CA-TO optimization problem using a game theoretic approach. Using the results in Part I [54], the contributions of Part II are as follows:…”

Section: A Contribution Of Part II Of This Two-part Papermentioning

confidence: 99%

“…I N Part I of this two-part series [54], we consider a system consisted of bidirectional wireless links that interfere with each other, and thoroughly analyze the joint transmission order (TO) selection and channel allocation (CA) problems from a game theoretic perspective. Here, in Part II, we focus on Device-to-Device (D2D) communications underlaying cellular networks, and present distributed and centralized joint CA-TO algorithms based on the findings in Part I [54], and examine their system performances.…”

Section: Introductionmentioning

confidence: 99%

“…Here, in Part II, we focus on Device-to-Device (D2D) communications underlaying cellular networks, and present distributed and centralized joint CA-TO algorithms based on the findings in Part I [54], and examine their system performances. The results of this paper can readily be applied to emerging Small Cell Networks (SCNs) and heterogeneous small-cell networks (Het-SNets) as well.…”

Section: Introductionmentioning

confidence: 99%

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Joint Optimization of Transmission-Order Selection and Channel Allocation for Bidirectional Wireless Links—Part II: Algorithms

Uykan

Jäntti

2014

IEEE Trans. Wireless Commun.

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This is the second in a two-part series of papers on transmission order (TO) optimization in the presence of channel allocation (CA), i.e., joint optimization of the TO selection and CA problem, for interfering bidirectional wireless links. Part I of this paper thoroughly analyzes the joint optimization problem from a game theoretic perspective for a general deterministic setting. Here in Part II, we present novel distributed and centralized CA-TO algorithms, together with their performance analysis, for Device-to-Device (D2D) communications underlaying cellular networks based on the findings in Part I of this paper. Here, TO is a novel dimension for optimization. In Part II, we propose and analyze novel two distributed and one centralized joint CA-TO algorithms. Our investigations show that: i) our algorithms contain many of the existing TO algorithms and CA algorithms as its special cases and can thus be considered as a general framework for the joint CA and TO optimization. The computer simulations for TDD-based D2D communications underlaying cellular network show that the proposed distributed and centralized joint CA-TO algorithms remarkably outperform the reference algorithms.Index Terms-Device-to-device (D2D) communications underlaying TDD cellular network, transmission order optimization, channel allocation problem, GADIA.

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“…In potential games, unilateral improvement dynamics is guaranteed to converge to a Nash equilibrium in a finite number of time steps when strategy sets are finite [10]. In [12]- [14], the improvement of signal-to-interference-plus-noise power ratio (SINR) using potential game-theoretic frameworks has been investigated. Moreover, in [15]- [18], channel allocation game for networks where nodes operate in HD mode (HD networks) are investigated.…”

Section: Introductionmentioning

confidence: 99%

Symmetric interaction in channel allocation for Bi-directional in-band full-duplex network

Sakaguchi

Yamamoto

Nishio

et al. 2015

2015 IEEE 26th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)

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An adaptive channel allocation scheme for bidirectional in-band full-duplex networks is proposed by modifying a channel allocation scheme for half-duplex networks on the basis of the property of bilateral symmetric interaction. To adapt schemes for half-duplex networks to full-duplex networks, we modify them so that channel update process successfully converges to a Nash equilibrium, i.e., it does not cycle. Specifically, the sum of products of transmission power and received interference power (instead of the sum of received interference power) at a communication pair is used as the novel payoff function. Then, the proposed channel allocation scheme is proved to be a potential game, and thus, the game is guaranteed to converge in a finite number of steps. Simulation results reveal that the proposed scheme is able to effectively allocate channels in bi-directional in-band full-duplex networks.

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Joint Optimization of Transmission-Order Selection and Channel Allocation for Bidirectional Wireless Links—Part I: Game Theoretic Analysis

Cited by 9 publications

References 26 publications

A Comprehensive Survey of Potential Game Approaches to Wireless Networks

A Comprehensive Survey of Potential Game Approaches to Wireless Networks

Joint Optimization of Transmission-Order Selection and Channel Allocation for Bidirectional Wireless Links—Part II: Algorithms

Symmetric interaction in channel allocation for Bi-directional in-band full-duplex network

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