{"title":"Joint relay selection and channel allocation in cooperative communication: A game theoretic learning solution","authors":"Cheng Ding, Liang Shen, Dianxiong Liu","doi":"10.1109/WCSP.2015.7341190","DOIUrl":null,"url":null,"abstract":"This article investigates the issue of joint relay selection and channel allocation in LTE relay networks, where the available channels of each node are restricted and heterogeneous. We decompose the issue into two subproblems: one is the channel selection of relay to mitigate the interference among relay nodes and another is joint relay and channel selection of source node to maximize the total capacity. The first subproblem is formulated as a global interaction game and a learning algorithm is proposed to achieve the Nash equilibrium. Based on the result of the first subproblem, the second one is formulated as a congestion game with player-specific payoff function. We propose a distributed solution to maximize the total capacity. Simulation results show that our approach can obtain a large total capacity and a high fairness index.","PeriodicalId":164776,"journal":{"name":"2015 International Conference on Wireless Communications & Signal Processing (WCSP)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Wireless Communications & Signal Processing (WCSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCSP.2015.7341190","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
This article investigates the issue of joint relay selection and channel allocation in LTE relay networks, where the available channels of each node are restricted and heterogeneous. We decompose the issue into two subproblems: one is the channel selection of relay to mitigate the interference among relay nodes and another is joint relay and channel selection of source node to maximize the total capacity. The first subproblem is formulated as a global interaction game and a learning algorithm is proposed to achieve the Nash equilibrium. Based on the result of the first subproblem, the second one is formulated as a congestion game with player-specific payoff function. We propose a distributed solution to maximize the total capacity. Simulation results show that our approach can obtain a large total capacity and a high fairness index.