论文标题
大规模MIMO涡轮增压器中的数据辅助LS通道估计
Data-Aided LS Channel Estimation in Massive MIMO Turbo-Receiver
论文作者
论文摘要
在本文中，我们提出了一种新的迭代最小二乘（LS）通道估计的新算法，该算法对64个天线大量输入，多重输出（MIMO）涡轮增压器。该算法采用了低密度奇迹检查（LDPC）解码器的对数 - 样本比（LLR）和最小平方误差（MMSE）估计器来实现软数据符号。这些软数据符号再次加入了MMSE加权，并与Pilot符号结合使用，以实现修改的LS通道估计。改进的LS估计值由同一信道估计单元使用，通过通道重新估计来增强涡轮接收器的性能，因此，所提出的方法具有较低的复杂性，并且适合任何通道估计解决方案，这在实践中非常有价值。我们分析了硬算法和软算法版本，并在Quadriga 2.0通道的3D-UMA模型中进行了5G涡轮接收器的模拟结果。与LS通道重新计算中未加权的硬数据符号使用相比，模拟结果表明高达0.3dB的性能增长。
In this paper, we propose a new algorithm of iterative least squared (LS) channel estimation for 64 antennas Massive Multiple Input, Multiple Output (MIMO) turbo-receiver. The algorithm employs log-likelihood ratios (LLR) of low-density parity-check (LDPC) decoder and minimum mean square error (MMSE) estimator to achieve soft data symbols. These soft data symbols are further MMSE-weighted again and combined with pilot symbols to achieve a modified LS channel estimate. The modified LS estimate is employed by the same channel estimation unit to enhance turbo-receiver performance via channel re-estimation, as a result, the proposed approach has low complexity and fits any channel estimation solution, which is quite valuable in practice. We analyze both hard and soft algorithm versions and present simulation results of 5G turbo-receiver in the 3D-UMa model of the QuaDRiGa 2.0 channel. Simulation results demonstrate up to 0.3dB performance gain compared to the unweighted hard data symbols utilization in the LS channel re-calculation.
