Blind channel identification based on higher-order cumulant fitting using genetic algorithms

Abstract

A family of blind equalisation algorithms identifies a channel model based on a higher-order cumulant (HOC) fitting approach. Since HOC cost functions are multimodal, gradient search techniques require a good initial estimate to avoid converging to local minima. We present a blind identification scheme which uses genetic algorithms (GAs) to optimise a HOC cost function. Because GAs are efficient global optimal search strategies, the proposed method guarantees to find a global optimal channel estimate. A micro-GA implementation is adopted to further enhance computational efficiency. As is demonstrated in computer simulation, this GA based scheme is robust and accurate, and has a fast convergence performance.