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Distributed Compressed Sensing-Based Channel Estimation and Pilot Allocation for MIMO Relay Networks

机译:基于分布式压缩的感应信道估计和用于MIMO中继网络的导频分配

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摘要

Distributed compressed sensing (DCS)-based channel estimation of multiple-input-multiple-output (MIMO) orthogonal frequency-division multiplexing for relay communication is considered in this paper. Specifically, the pilot allocation is addressed to optimize the channel estimation performance. Pilot placement in all the existing works based on Compressed Sensing (CS), address the mean square error (MSE) probabilistically via mutual coherence. On the contrary, we try to address the MSE of the estimate directly and optimize the MSE directly and design a pilot pattern to maximize the performance of the estimation. By taking into account the optimization approach, a combinatorial stochastic algorithm has been presented. Simulation results represent that the DCS-based MIMO relay channel estimation using optimized pilot placements will increase the performance from 3 to 10 dB as compared with the conventional least squares (LS) method. Moreover, the DCS-based MIMO relay channel estimation shows 2.3% and 45% improvement in spectrum efficiency under the same bit error rate performance over the compressed sensing (CS)-based channel estimation and traditional LS-based channel estimation approach, respectively.
机译:本文考虑了用于中继通信的多输入多输出(MIMO)正交频分复用的分布式压缩感应(DCS)的基于信道估计。具体地,解决了导频分配以优化信道估计性能。基于压缩感测(CS)的所有现有工程中的导频安置,通过相互连贯地址地址均方误差(MSE)概率。相反,我们尝试直接解决估计的MSE并直接优化MSE,并设计飞行员模式以最大化估计的性能。通过考虑优化方法,已经介绍了组合随机算法。仿真结果表示,与传统最小二乘(LS)方法相比,使用优化的导频放置的基于DCS的MIMO中继信道估计将增加3到10dB的性能。此外,基于DCS的MIMO继电器信道估计分别在相同的钻头误差率性能下分别在压缩感测(CS)的信道估计和基于传统的LS的信道估计方法中的相同比特误差率性能下的2.3%和45%。

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