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Learning to be energy-efficient in cooperative networks

Research output: Contribution to journalJournal article

Published
  • Daxin Tian
  • Jianshan Zhou
  • Zhengguo Sheng
  • Qiang Ni
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<mark>Journal publication date</mark>12/2016
<mark>Journal</mark>IEEE Communications Letters
Issue number12
Volume20
Number of pages4
Pages (from-to)2518-2521
Publication statusPublished
Early online date13/09/16
Original languageEnglish

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.

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©2016 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.