利用数据和导频的多小区Massive MIMO系统信道估计

本文提出一种通过同时利用上行数据和导频进行信道估计来对抗时分双工大规模多输入多输出（Massive multi-input multi-output，Massive MIMO）系统中导频污染的方法。考虑到Massive MIMO系统下空间相关信道在角度域具有近似稀疏性，期望用户信道和干扰信道的多径分量因而可分辨。同时上行数据子帧中的数据符号数远大于导频序列的长度。基于以上两点观察，首先利用上行导频对信道进行粗估计，然后将解码得到的上行数据符号视为导频序列，用于得到角度域信道估计中能量较大分量所处的位置。通过抽取信道粗估计中相应位置上的信道系数，可以得到信道的精估计。仿真表明，无论相邻小区采用同一组正交导频序列、还是不同组但具有相关性的导频序列，所提出的信道估计方法都能有效地消除导频污染。 

Data and Pilot-Aided Channel Estimation for Multi-cell Massive MIMO System

This paper proposed a both data- and pilot-aided channel estimation to deal with pilot contamination in time-division duplex massive multi-input multi-output (MIMO) systems. The paths of the desired user are distinguishable from those of interference users due to the approximate sparse nature in angle-domain of the spatial correlated massive MIMO channels, while the length of an uplink sub-frame is much larger than that of the pilot sequence. We proposed to first roughly estimate the channel by using uplink pilot sequence. Then, we regard the decoded uplink data symbols as the pilot sequence to find the positions of the significant coefficients in the angle-domain channel estimate. By extracting the corresponding channel components from the rough channel estimate, a refined channel estimate is obtained. Simulation results show that pilot contamination can be largely removed by the proposed channel estimate, no matter whether the same group of orthogonal pilot sequences are reused or different groups of pilot sequences with cross-correlation are applied among adjacent cells.