论文标题
基于粒子滤波器的大规模MIMO通道估计
Particle Filter based Massive MIMO Channel Estimation
论文作者
论文摘要
最近，在下一代无线通信中引起了大量的多输入多输出（MIMO）通信系统。在大量的MIMO中使用大量天线使频道状态信息的估计非常具有挑战性。准确的渠道状态信息对于资本化大型MIMO技术的优势至关重要。本文提出了集合平方根滤波器（ENSRF）和ENSRF的变体的应用，即集合方形根滤波器（PUENSRF）的粒子明智的更新版本，以估计大量MIMO场景中的时间选择性频率 - 频率淡淡的褪色通道系数。仿真结果清楚地表明，与常规粒子过滤器相比，PUENSRF估计值的较高精度和滤光度收敛。
Massive multiple-input multiple-output (MIMO) communication systems have drawn significant interest recently in next-generation wireless communications. The use of a large number of antennas in massive MIMO makes the estimation of channel state information very challenging. Accurate channel state information is essential in capitalizing the advantages of the massive MIMO technology. This paper proposes the application of the Ensemble Square Root Filter (EnSRF) and a variant of EnSRF, namely a Particle wise Update version of the Ensemble Square Root Filter (PUEnSRF) to estimate the time-selective frequency-flat fading channel coefficients in the massive MIMO scenario. Simulation results clearly indicate the remarkably superior accuracy and filter convergence of PUEnSRF estimates as compared to the conventional particle filters.
