面向5G超密集网络的分布式中继选择方法
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摘要
该文研究了面向5G超密集网络的分布式中继选择问题。从博弈论的角度出发,将问题建立成非合作博弈模型,纳什均衡是非合作博弈模型中常用的稳态解。文章利用线性对数学习算法能在无需信息交互的情况下获得稳态解。仿真结果表明,所提线性对数学习算法是完全分布式实现的,且获得的全网吞吐量优于现有的分布式优化方法,并接近于传统的集中式优化方法。
The problem of distributed relay selection for Ultra-dense 5G network was investigated in this literature.The problem was formulated as a non-cooperative game.The proposed game model possess Nash equilibrium which is the well-known stable solution to the non-cooperative game.Then the Linear Log Learning algorithm was used to achieve the stable solution without information exchange.Simulation results the Linear Log Learning algorithm is completely distributed.Moreover the expected network capacity achieve by the proposed approach is Outperforms the distributed algorithm in existence and is close to the centralized algorithm traditionally.
The problem of distributed relay selection for Ultra-dense 5G network was investigated in this literature.The problem was formulated as a non-cooperative game.The proposed game model possess Nash equilibrium which is the well-known stable solution to the non-cooperative game.Then the Linear Log Learning algorithm was used to achieve the stable solution without information exchange.Simulation results the Linear Log Learning algorithm is completely distributed.Moreover the expected network capacity achieve by the proposed approach is Outperforms the distributed algorithm in existence and is close to the centralized algorithm traditionally.
引文
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[8]J.Nash.Non-cooperative games[D].Annals of mathematics,1951:286-295.
[9]Yu H X,Qi H W,Liang S,et al.Robust Multiuser Sequential Channel Sensing and Access in Dynamic Cognitive Radio Networks:Potential Games and Stochastic Learning[J].IEEETransactionson Vehicular Technology,2014,64(8):3594-3607.
[10]Wu C L,Lin T N,Liu H F,et al.On relay assignment strategy in wireless cellular environment[A].In:Computing,Networking and Communications(ICNC),2014 International Conference on[C].IEEE,2014:698-703.
[2]Access E U T R.Further advancements for E-UTRA physical layer aspects[R].3GPP TR 36.814,2010.
[3]Yang D,Fang X,Xue G.OPRA:Optimal Relay Assignment for Capacity Maximization in Cooperative Networks[A].In:2011 IEEE International Conference on Communications(ICC)[C].IEEE,2011,57(4):1-6.
[4]Chen Z,Lin T,Wu C.Decentralized Learning-Based Relay Assignment for Cooperative Communications[J].IEEE Transactions on Vehicular Technology,2016,65(2):813-826.
[5]Laneman J N,Wornell G W,Tse D N C.An efficient protocol for realizing cooperative diversity in wireless networks[A].In:Proceedings of 2001 IEEE International Symposium on Information Theory[C].IEEE,2001:294.
[6]Sendonaris A,Erkip E,Aazhang B.User cooperation diversity.Part I.System description[J].IEEE Transactions on Communications,2003,51(11):1927-1938.
[7]Laneman J N,Tse D N C,Wornell G W.Cooperative diversity in wireless networks:Efficient protocols and outage behavior[J].IEEE Transactions on Information Theory,2004,50(12):3062-3080.
[8]J.Nash.Non-cooperative games[D].Annals of mathematics,1951:286-295.
[9]Yu H X,Qi H W,Liang S,et al.Robust Multiuser Sequential Channel Sensing and Access in Dynamic Cognitive Radio Networks:Potential Games and Stochastic Learning[J].IEEETransactionson Vehicular Technology,2014,64(8):3594-3607.
[10]Wu C L,Lin T N,Liu H F,et al.On relay assignment strategy in wireless cellular environment[A].In:Computing,Networking and Communications(ICNC),2014 International Conference on[C].IEEE,2014:698-703.