Sum rate maximization antenna selection via discrete stochastic approximation in MIMO two-way AF relay with imperfect CSI

Gang Liu, Hong Ji, Yi Li, Xiaoliang Zhang
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引用次数: 11

Abstract

Recently, the MIMO two-way AF relaying, a promising spectral efficient transmission technique, has attracted a great deal of attention. Meanwhile, it has been shown that it is possible to improve the performance of MEMO systems by employing antenna selection technology. Existing antenna selection algorithms in MEMO two-way AF relay assume perfect channel state information(CSI). However, as a matter of fact, it is difficult to obtain perfect CSI. In this paper, considering the antenna correlation and channel estimation error, we derive the lower bound on sum rate utilizing worst case uncorrelated additive noise theorem in MIMO two-way AF relaying system, and analyze the effect of antenna correlation and channel estimation error on the sum rate. Then, an optimal relay antenna selection algorithm based on discrete stochastic optimization is proposed to maximize the sum rate under the assumption of imperfect CSI. We also prove the convergence of the proposed algorithm through theoretical analysis. Through extensive numerical simulation, we observe that the proposed relay antenna selection algorithm converges to the best antenna set obtained by exhaustive search when only imperfect CSI is available.
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基于离散随机逼近的不完全CSI MIMO双向AF中继和速率最大化天线选择
近年来,MIMO双向自动对焦中继作为一种很有前途的频谱高效传输技术受到了广泛的关注。同时,研究表明采用天线选择技术可以提高MEMO系统的性能。现有的MEMO双向自动对焦中继天线选择算法假设了完美的信道状态信息。然而,事实上,很难获得完美的CSI。在考虑天线相关和信道估计误差的情况下,利用最坏情况下不相关加性噪声定理推导了MIMO双向自动对焦中继系统和速率的下界,并分析了天线相关和信道估计误差对和速率的影响。然后,提出了一种基于离散随机优化的中继天线最优选择算法,在不完全CSI假设下使和速率最大化。并通过理论分析证明了算法的收敛性。通过大量的数值模拟,我们观察到所提出的中继天线选择算法在只有不完全CSI可用时收敛于穷举搜索得到的最佳天线集。
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