Maximum Likelihood Based Measurement of Interference Level and Noise Power for Memoryless Gaussian Channel with Deterministic Interference

摘要

The model of memoryless Gaussian channel with deterministic interference are common in various engineering applications. In this letter we propose a non-data-aided algorithm for joint measurement of the interference level and the noise power. The algorithm applies an iterative approach based on the maximum likelihood criterion. The Cramer-Rao bound (CRB) is also derived as the performance benchmark. Simulation results show that the proposed approach has fast convergence speed and its measurement performance is almost identical to the CRB.