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Performance analysis of non-coherent MIMO MRC scheme with training using finite-SNR diversity and multiplexing tradeoff

机译:非相干MIMO MRC方案的有限信噪比分集和复用折衷训练的性能分析

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摘要

The inherent tradeoff between the twin benefits offered by multiple antenna systems, namely, the diversity gain and the multiplexing gain is captured as the diversity multiplexing tradeoff (DMT). The DMT at asymptotically high signal-to-noise ratio (SNR) is optimistic, whereas at finite SNR, it is practical. In this paper, point-to-point multiple input multiple output (MIMO) systems are considered under the assumption of coherent and non-coherent communication implying, respectively, whether perfect channel state information is available at the receiver (CSIR) or not. The literature mainly addresses noncoherent communication with training at asymptotically high SNR, whereas the finite-SNR analysis is more relevant in practice. We address the performance analysis of a MIMO maximal ratio combining scheme by deriving closed-form expressions of the DMT at finite SNR under non-coherent communication with training. At a fixed multiplexing gain and finite SNR, a reduction in the diversity gain is observed when coherent communication is replaced by non-coherent communication with training. We also show that for a high multiplexing gain, the reduction in diversity gain is much more pronounced as compared to that at a low multiplexing gain. A training-based channel estimation scheme discussed in the literature is used in two modes of power allocation, namely, the capacity optimal power allocation and equal power allocation (EPA). In both modes, at a fixed average SNR and with equal duration of training, we observe that the power allocation mode does not make a significant impact on the finite-SNR DMT of the MIMO scheme. We also observe that in the EPA mode, the diversity gain reduces with increase in training duration.
机译:由多个天线系统提供的双倍益处之间的固有折衷,即分集增益和复用增益被捕获为分集复用权衡(DMT)。渐近高信噪比(SNR)的DMT是乐观的,而在有限SNR时,它是实用的。在本文中,在相干和非相干通信的假设下分别考虑点对点多输入多输出(MIMO)系统,这分别意味着在接收器(CSIR)上是否可获得完美的信道状态信息。文献主要讨论了在渐近高SNR的情况下进行训练的非相干通信,而在实践中,有限SNR分析则更为重要。我们通过推导非相干通信下有限信噪比下DMT的闭式表达式,来解决MIMO最大比合并方案的性能分析。在固定的复用增益和有限SNR的情况下,当用训练的非相干通信代替相干通信时,会观察到分集增益的降低。我们还表明,对于高复用增益,与低复用增益相比,分集增益的降低更为明显。文献中讨论的基于训练的信道估计方案用于两种功率分配模式,即容量最优功率分配和等功率分配(EPA)。在这两种模式下,在固定的平均SNR且训练时间相等的情况下,我们观察到功率分配模式对MIMO方案的有限SNR DMT不会产生重大影响。我们还观察到在EPA模式下,多样性增益随训练时间的增加而降低。

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