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Optimal power control for wireless cooperative relay networks: a cooperative game theoretic approach
Author(s) -
Zhang Guopeng,
Li Ping,
Zhou Dongdai,
Yang Kun,
Ding Enjie
Publication year - 2013
Publication title -
international journal of communication systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.344
H-Index - 49
eISSN - 1099-1131
pISSN - 1074-5351
DOI - 10.1002/dac.2316
Subject(s) - computer science , relay , node (physics) , bargaining problem , computer network , game theory , nash equilibrium , transmitter power output , power control , non cooperative game , wireless , transmission (telecommunications) , resource allocation , power (physics) , wireless network , mathematical optimization , telecommunications , transmitter , mathematical economics , channel (broadcasting) , physics , mathematics , structural engineering , quantum mechanics , engineering
SUMMARY Wireless nodes operating on batteries are always assumed to be selfish to consume their energy solely to maximize their own benefits. Thus, the two network objectives, that is, system efficiency and user fairness should be considered simultaneously. To this end, we propose two game theoretic mechanisms, that is, the signal‐to‐noise ratio (SNR) game and the data‐rate game to stimulate cooperation among selfish user nodes for cooperative relaying. Considering one node could trade its transmission power for its partner's relaying directly, the strategy of a node is defined as the amount of power that it is willing to contribute for relaying purpose. In the SNR game, selfish nodes are willing to achieve SNR increases at their receivers, while in the data‐rate game the nodes are willing to achieve data‐rate gains. We prove that each of the games has a unique Nash bargaining solution. Simulation results show that the Nash bargaining solution lead to fair and efficient resource allocation for both the cooperative partner nodes in the Pareto optimal sense, that is, both the nodes could experience better performance than they work independently and the degree of cooperation of a node only depends on how much contribution its partner can make to improve its own performance. Copyright © 2012 John Wiley & Sons, Ltd.