BLIND EQUALIZERS WITH SIMULATED ANNEALING OPTIMIZATION FOR DIGITAL-COMMUNICATION SYSTEMS

New batch-type methods and their recursive extensions are introduced for blind equalization of digital communication channels. Based on the underlying cost function of the existing Bussgang and cumulant-fitting algorithms, simulated annealing (SA) optimization is successfully employed to identify and equalize the communication channels. Many of the existing blind equalization algorithms utilize a stochastic gradient approach to minimize non-linear cost functions. Owing to the multimodal nature of these functions, the gradient algorithms might converge to the wrong solution. In contrast, the proposed methods are based on a global optimization algorithm. The SA algorithm tends to avoid the local minima encountered. The feasibility and convergence behaviour of the proposed algorithms are examined by means of computer simulations. Computational complexity issues in the implementation of the algorithms are discussed.