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Channel Estimation Based on Quantized MMP for FDD Massive MIMO Downlink

机译:基于量化MMP的FDD大规模MIMO下行链路的信道估计

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In this paper, we consider channel estimation for Massive MIMO systems operating in frequency division duplexing mode. By exploiting the sparsity of propagation paths in Massive MIMO channel, we develop a compressed sensing (CS) based channel estimator which can reduce the pilot overhead. As compared with the conventional least squares (LS) and linear minimum mean square error (LMMSE) estimation, the proposed algorithm is based on the quantized multipath matching pursuit (MMP) reduced the pilot overhead and performs better than other CS algorithms. The simulation results demonstrate the advantage of the proposed algorithm over various existing methods including the LS, LMMSE, CoSaMP and conventional MMP estimators.
机译:在本文中,我们考虑在频分双工模式下运行的大型MIMO系统的信道估计。通过利用大规模MIMO信道中的传播路径的稀疏性,我们开发了一种基于压缩的感测(CS)的信道估计,可以减少导频开销。与传统最小二乘(LS)和线性最小均方误差(LMMSE)估计相比,所提出的算法基于量化的多径匹配追踪(MMP)降低了导频开销并且比其他CS算法更好地执行。仿真结果证明了所提出的算法在包括LS,LMMSE,COSAMP和传统MMP估计的各种现有方法上的优点。

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