We consider massive multiple-input multiple-output (MIMO) systems in the presence of Cauchy noise. First, we focus on the channel estimation problem. In the standard massive MIMO setup, the users transmit orthonormal pilots during the training phase and the received signal at the base station is projected onto each pilot. This processing is optimum when the noise is Gaussian. We show that this processing is not optimal when the noise is Cauchy and as a remedy propose a channel estimation technique that operates on the raw received signal. Second, we derive uplink-downlink achievable rates in the presence of Cauchy noise for perfect and imperfect channel state information. Finally, we derive log-likelihood ratio expressions for soft bit detection for both uplink and downlink, and simulate coded bit-error-rate curves. In addition to this, we derive and compare the symbol detectors in the presence of both Gaussian and Cauchy noises. An important observation is that the detector constructed for Cauchy noise performs well with both Gaussian and Cauchy noises; on the other hand, the detector for Gaussian noise works poorly in the presence of Cauchy noise. That is, the Cauchy detector is robust against heavy-tailed noise, whereas the Gaussian detector is not.

翻译：本文研究了存在柯西噪声的大规模多输入多输出系统。首先，聚焦于信道估计问题。在标准大规模MIMO配置中，用户需在训练阶段发送正交导频，基站将接收信号投影至各导频。该处理在噪声为高斯分布时最优。我们证明当噪声为柯西分布时该处理并非最优，并据此提出一种基于原始接收信号的信道估计技术。其次，推导了在完美与非完美信道状态信息条件下，存在柯西噪声时的上下行可达速率。最后，推导了上下行软比特检测的对数似然比表达式，并仿真了编码误码率曲线。此外，我们推导并对比了高斯噪声与柯西噪声共存环境下的符号检测器。重要发现是：针对柯西噪声设计的检测器在高斯与柯西噪声下均表现优异；而针对高斯噪声设计的检测器在柯西噪声环境下性能极差。这表明柯西检测器对重尾噪声具有鲁棒性，而高斯检测器不具备该特性。