Rayleigh Channel Statistics Estimation Using SINR Samples Under Single Interference

Abstract

In this paper, we tackle the problem of the signal-to-interference-plus-noise ratio (SINR) distribution estimation under flat Rayleigh fading with a single interferer. Assuming that we collect a set of SINRs’ values from the receiver, the distribution is parametrized by the direct and interfering channel magnitude that need to be estimated. To that purpose, we propose here two new estimators: the maximum likelihood estimator (MLE) and a method of moments (MoM) estimator. For both estimators we derive the equations and propose a numerical implementation scheme based on Newton’s algorithm. The MoM estimator is less complex but also less accurate, whereas the MLE is more accurate but requires careful initialization. Thus, we propose to use the MoM’s estimates to initialize the MLE algorithm. In addition, we derive the Cramer-Rao lower bound (CRLB) associated to this estimation problem and propose an efficient computation of it. We provide simulations to assess the performance of our proposed estimators and verify that the mean square error of the MLE is close to the CRLB.