Title :
Blind channel identification based on higher-order cumulant fitting using genetic algorithms
Author :
Chen, S. ; McLaughlin, Steve
Author_Institution :
Dept. of Electr. & Electron. Eng., Portsmouth Univ.
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
Keywords :
convergence of numerical methods; equalisers; genetic algorithms; higher order statistics; parameter estimation; search problems; telecommunication channels; HOC cost functions; blind channel identification; blind equalisation algorithms; computational efficiency; convergence performance; genetic algorithms; global optimal channel estimate; global optimal search strategies; higher-order cumulant fitting; micro-GA implementation; Blind equalizers; Computer simulation; Convergence; Cost function; Design methodology; Genetic algorithms; Genetic engineering; Maximum likelihood estimation; Nonlinear filters; Robustness;
Conference_Titel :
Higher-Order Statistics, 1997., Proceedings of the IEEE Signal Processing Workshop on
Conference_Location :
Banff, Alta.
Print_ISBN :
0-8186-8005-9
DOI :
10.1109/HOST.1997.613512