Communication over non-Gaussian channels - Part II: Channel estimation, mismatched receivers, and error performance with coding

Limited wireless spectrum coupled with the need to support co-existence mechanisms call for robust receivers and improved interference management. With a spectrum sharing operating mode, it is hard to model dynamic interference conditions in wireless networks. In the first part of this work, we have introduced an additive non-Gaussian channel (ANGC) model that captures a variety of interference sources, and presented average mutual information and average probability of error expressions when the receiver has perfect channel estimates and no knowledge of the noise statistics. The primary goal of introducing this model is to compactly represent a wide range of non-Gaussian noise sources in a robust and simple manner. As a continuation of that work, in this paper, we consider the problem of noise variance estimation, signal detection with pilot-assisted channel estimation (PACE), and coded sequence detection with a mismatched decoding metric. We derive the joint maximum-likelihood estimates of the Gaussian noise variance and the non-Gaussian parameter, and expressions for the outage probability and the average bit error probability for uncoded binary signaling. We also derive expressions for the average pairwise error probability with coding and PACE on ANGC. Numerical and simulation results are presented to validate the analysis presented in this paper.