Massive MIMO antennas in cellular systems help support a large number of users in the same time-frequency resource and also provide significant array gain for uplink reception. However, channel estimation in such large antenna systems can be tricky, not only since pilot assignment for multiple users is challenging, but also because the pilot overhead especially for rapidly changing channels can diminish the system throughput quite significantly. A pilotless transceiver where the receiver can perform blind demodulation can solve these issues and boost system throughput by eliminating the need for pilots in channel estimation. In this paper, we propose an iterative matrix decomposition algorithm for the blind demodulation of massive MIMO OFDM signals. This new decomposition technique provides estimates of both the user symbols and the user channel in the frequency domain simultaneously (to a scaling factor) without any pilots. Simulation results demonstrate that the lack of pilots does not affect the error performance of the proposed algorithm when compared to maximal-ratio-combining (MRC) with pilot-based channel estimation across a wide range of signal strengths.

翻译：蜂窝系统中的大规模MIMO天线有助于在同一时频资源上支持大量用户，并为上行链路接收提供显著的阵列增益。然而，此类大规模天线系统中的信道估计可能较为棘手，这不仅是因为多用户的导频分配具有挑战性，还因为导频开销（尤其是在信道快速变化的情况下）会显著降低系统吞吐量。一种无需导频的收发机（接收端可进行盲解调）能够解决这些问题，并通过消除信道估计中导频的需求来提升系统吞吐量。本文提出了一种用于大规模MIMO OFDM信号盲解调的迭代矩阵分解算法。这种新的分解技术能够在频域中同时（至多一个缩放因子）估计用户符号和用户信道，而无需任何导频。仿真结果表明，与基于导频信道估计的最大比合并（MRC）相比，在广泛的信号强度范围内，所提算法的误差性能不受缺少导频的影响。