Tian, Daxin and Zhou, Jianshan and Sheng, Zhengguo and Ni, Qiang (2016) Learning to be energy-efficient in cooperative networks. IEEE Communications Letters, 20 (12). pp. 2518-2521. ISSN 1089-7798
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Abstract
Cooperative communication has great potential to improve the transmit diversity in multiple users environments. To achieve a high network-wide energy-efficient performance, this letter poses the relay selection problem of cooperative communication as a noncooperative automata game considering nodes’ selfishness, proving that it is an ordinal game (OPG), and presents a game-theoretic analysis to address the benefit-equilibrium decision-making issue in relay selection. A stochastic learning-based relay selection algorithm is proposed for transmitters to learn a Nash-equilibrium strategy in a distributed manner. We prove through theoretical and numerical analysis that the proposed algorithm is guaranteed to converge to a Nash equilibrium state, where the resulting cooperative network is energy-efficient and reliable. The strength of the proposed algorithm is also confirmed through comparative simulations in terms of energy benefit and fairness performances.