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Antenna selection for space-time coded systems with imperfect channel estimation

机译:信道估计不完善的时空编码系统的天线选择

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This paper studies the performance of antenna selection (AS) for space-time (ST) coded systems with noisy channel estimates. For coherent AS systems over Rayleigh flat fading channels, we derive the pairwise error probability (PEP) in the presence of imperfect channel estimation, where the channel is estimated using training insertion and minimum mean square error (MMSE) estimation. Multiplexed training is employed, where the antennas are multiplexed to the small number of RF chains available in the AS system. AS is performed only at the receiver, using the maximum estimated channel power selection rule. Both the maximum likelihood (ML) decoder taking into account the channel estimation error, and the minimum distance decoder are considered, and full diversity gain is shown to be preserved for both cases. Based on the derived training-based PEP, the effective SNR and the coding gain loss due to training are quantified for square unitary and orthogonal codes. The optimal power allocation between the training and data symbols is obtained by minimizing the PEP. For AS systems employing orthogonal designs, we further derive the exact PEP expression in closed-form. We also show that when square unitary training is employed, AS using the norm of MMSE channel estimates is equivalent to AS using the norm (power) of the received signal. Exploiting this fact, we propose an alternate training scheme which avoids multiplexing, has higher spectral efficiency, and better performance compared to the multiplexed training scheme. Simulations are shown to validate our analysis
机译:本文研究具有噪声信道估计的空时(ST)编码系统的天线选择(AS)性能。对于瑞利平坦衰落信道上的相干AS系统,我们在存在不完善信道估计的情况下得出成对错误概率(PEP),其中使用训练插入和最小均方差(MMSE)估计来估计信道。采用多路复用训练,其中天线被多路复用到AS系统中可用的少量RF链。使用最大估计信道功率选择规则,仅在接收机上执行AS。考虑了信道估计误差的最大似然(ML)解码器和最小距离解码器均被考虑,并且两种情况的全分集增益均被保留。基于派生的基于训练的PEP,针对平方unit码和正交码对有效SNR和训练导致的编码增益损失进行了量化。通过最小化PEP,可以获得训练和数据符号之间的最佳功率分配。对于采用正交设计的AS系统,我们进一步导出了封闭形式的精确PEP表达式。我们还表明,当采用平方unit训练时,使用MMSE信道估计范数的AS与使用接收信号范数(功率)的AS等效。利用这一事实,我们提出了一种替代的训练方案,该方案比复用训练方案避免了复用,具有更高的频谱效率和更好的性能。仿真显示可以验证我们的分析

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