Joint MMSE transmit diversity optimization and relay selection for cooperative MIMO systems using discrete stochastic algorithms

P. Clarke, R. D. Lamare
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Abstract

This paper presents joint transmit diversity selection (TDS) and relay selection (RS) algorithms based on discrete stochastic optimization for a multi-relay cooperative MIMO system. A two-phase, decode-and-forward (DF) network with a non-negligible direct path is considered where linear minimum mean square error (MMSE) receivers are used at all nodes. TDS and RS are performed jointly with continuous least squares channel estimation and no transmit preprocessing is required. RS removes relays from consideration by TDS and generates an optimized set from which TDS is made, improving the convergence, performance, complexity and energy consumption of the TDS process whilst maintaining low feedback requirements. The performance of the proposed schemes is evaluated via mean square error (MSE), bit-error rate (BER) and complexity comparisons. The results show that the proposed schemes outperform cooperative transmission with and without TDS in terms of diversity, MSE and BER, and match that of the optimum exhaustive solutions whilst making considerable complexity and energy savings.
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基于离散随机算法的联合MMSE发射分集优化与中继选择
针对多中继协同MIMO系统,提出了基于离散随机优化的联合发射分集选择(TDS)和中继选择(RS)算法。考虑了一种具有不可忽略直接路径的两相解码转发(DF)网络,其中所有节点都使用线性最小均方误差(MMSE)接收器。TDS和RS结合连续最小二乘信道估计,不需要进行传输预处理。RS将继电器从TDS的考虑中移除,并生成一组优化的TDS,从而提高TDS过程的收敛性、性能、复杂性和能耗,同时保持较低的反馈要求。通过均方误差(MSE)、误码率(BER)和复杂度比较对所提方案的性能进行了评价。结果表明,所提出的方案在分集、MSE和BER方面都优于有TDS和没有TDS的合作传输,并与最优的详尽解决方案相匹配,同时具有相当的复杂性和节能性。
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