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

Massive MIMO with Cauchy Noise: Channel Estimation, Achievable Rate and Data Decoding