Pricing Games for Distributed Cooperative Transmission

Ng, Cho Yiu; Lok, Tat-Ming; Wong, T.F.

doi:10.1109/tvt.2010.2049757

Cited by 14 publications

(12 citation statements)

References 44 publications

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“…Other problems that have been formulated in terms of potential games are found in routing [9], [97], [156], [157], [186], [203], BS/AP selection [98], [99], [112], [161], [172], cooperative transmissions [4], [139], secrecy rate maximization [11], code design for radar [146], broadcasting [35], spectrum market [87], network coding [115], [147], [148], data cashing [94], social networks [40], computation offloading [42], localization [79], and demand-side management in smart grids [77], [183]. …”

Section: Discussionmentioning

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: Discussionmentioning

confidence: 99%

A Comprehensive Survey of Potential Game Approaches to Wireless Networks

Yamamoto

2015

IEICE Trans. Commun.

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“…It should be pointed out that game G differs from many conventional non-cooperative game models where players' utilities couple with each other but strategy spaces are independent (see, e.g., [16]). In contrast, it is interesting to note that players in game G have coupled strategy spaces but their associated utilities are independent.…”

Section: Flow Directionmentioning

confidence: 99%

“…In contrast, it is interesting to note that players in game G have coupled strategy spaces but their associated utilities are independent. Therefore, the approach used in [16] cannot be directly applied in this article. Instead, we resort to other approaches to tackle game G, especially in distributed algorithms design, as shown in the forthcoming sections.…”

Section: Flow Directionmentioning

confidence: 99%

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Distributed wireless information flow allocation in multiple access networks

Lin

Lok

2011

J Wireless Com Network

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We present a general framework for distributed wireless information flow allocation problem in multiple access networks, where the end users (EUs) can seek wireless flows from multiple access points (APs). We aim to minimize the power consumption while satisfying each EU's minimum data rate requirement but not violating peak power constraint of each AP and interference constraint monitored by regulatory agents. Toward this end, we model the flow allocation problem as a game which is proved to be a best-response potential game. Then based on potential game theory, we show the existence and uniqueness of Nash equilibrium in the formulated game. Moreover, we demonstrate that the Nash equilibrium is actually the globally optimal solution to our problem. Besides, we propose two distributed algorithms along with convergence analysis for the network to obtain the Nash equilibrium. Meanwhile, we reveal the interesting layered structure of the problem in question. Extensive numerical results are conducted to demonstrate the benefits obtained by flow allocation, as well as the effectiveness of our proposed algorithms.

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“…Practically, the available relay nodes may not cooperate and share their power unless provided with some reimbursement. 24 This motivated us to propose an incentive-based CG for optimal power allocation in multirelay cooperative networks. In this paper, we have formulated an integrated game theoretic framework based on SG and CG.…”

Section: Introductionmentioning

confidence: 99%

A coalitional game‐based integrated framework for optimal power allocation in multirelay cooperative environment

Lamba

Kumar

Sharma

2017

Int J Communication

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SummaryCooperative relaying has emerged as an efficient transmit strategy in wireless networks affected by fading. In multirelay scenarios, the performance of cooperative systems is heavily influenced by resource allocation among the available relays. However, in practical scenarios, a relay may not help unless the cooperation improves its own utility. To address the above problem, this paper introduces a novel integrated game-theoretic framework that involves incentivebased optimal power allocation among the cooperating relays. Coalition formation game has been used to model the cooperation among relays that is integrated into a Stackelberg game, for considering the benefits of source and relays jointly. The game theoretic framework has been implemented with an objective to find an optimal and stable coalition set of relays that not only maximizes their utilities but also helps the source to allocate the optimal power to the relays at the optimal price, thereby increasing its utility too. Simulation results have confirmed that the proposed game theoretic solutions achieve comparable performance in system throughput as compared with the centralized approach. Relay communication is a promising exemplar for future wireless networks. Through relaying, cooperative communication can enhance performance, reduce battery consumption, increase network lifetime, and improve throughput of the systems. 1 Ubiquitous systems defined by International Telecommunication Union require at least 10 times higher data rate than that fulfilled in legacy cellular networks. To obtain such high data rates without increasing the number of base stations and operating costs, it is necessary to introduce relay-assisted communication in general and cooperation between individual relays in particular. The relay-based architecture and cooperative multipath technologies have attracted much attention worldwide. Today, most of the standards for future mobile communication systems viz 3GPP, 3GPP2, B3G, and 4G, Wireless Local Area Network, and broadband wireless networks (IEEE 802.16j) utilize the concept of relaying and frequently take into account the problems related to relay-assisted communication and cooperation. 2 The Wireless World Initiative New Radio project has a detailed planning for ubiquitous broadband mobile radio relaying system. 3 In relay systems, energy efficiency is considered as one of the most important issues because the power of mobile users is a scarce and limited resource. 4 With the combination of relaying and other emerging technologies,

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Pricing Games for Distributed Cooperative Transmission

Cited by 14 publications

References 44 publications

A Comprehensive Survey of Potential Game Approaches to Wireless Networks

A Comprehensive Survey of Potential Game Approaches to Wireless Networks

Distributed wireless information flow allocation in multiple access networks

A coalitional game‐based integrated framework for optimal power allocation in multirelay cooperative environment

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