Game Theoretic Multimode Precoding Strategy Selection for MIMO Multiple Access Channels
Game Theoretic Multimode Precoding Strategy Selection for MIMO Multiple Access Channels
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DOI：
10.1109/lsp.2010.2047315
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发表时间：
2010-04
影响因子：
3.9
通讯作者：
Wei Zhong;Youyun Xu;M. Tao;Yueming Cai
中科院分区：
文献类型：
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作者：
Wei Zhong;Youyun Xu;M. Tao;Yueming Cai
本文关注多输入多输出（MIMO）多址信道的多模式预编码策略的分散式选择。我们将其表述为一个离散的非合作博弈。该博弈被证明至少存在一个纯策略纳什均衡（NE），并且使和速率最大化的最优策略组合构成一个纯策略NE。然后我们提出一种基于学习自动机的分散式算法来实现该NE。引入一种重复机制以提高和速率性能，并设计一种调整步长的机制来控制收敛速度。仿真结果表明，所提出的仅需有限反馈的算法能够实现接近最优或最优的和速率性能。
This paper is concerned with decentralized selection of multimode precoding strategy for multiple-input multiple-output (MIMO) multiple access channels. We formulate it as a discrete noncooperative game. This game is shown to possess at least one pure strategy Nash equilibrium (NE) and the optimal strategy profile which maximizes the sum rate constitutes a pure strategy NE. Then we propose a decentralized algorithm based on learning automata to achieve the NE. A repeated mechanism is introduced to improve the sum rate performance and a mechanism for adapting step size is designed to control the convergence speed. Simulation results show that the proposed algorithm, which only requires limited feedback, can achieve near optimal or optimal sum rate performance.