Fast Converging Filtered Regressor Algorithms for Blind Equalization

We present a simple extension of standard Bussgang blind equalization algo rithms that signi cantly improves their convergence properties Our technique uses the inverse channel estimate to lter the regressor signal The modi ed algorithms provide quasi Newton convergence in the vicinity of a local minimum of the chosen cost function with only a modest increase in the overall computational complexity of the system An example of the technique as applied to the constant modulus algorithm indicates its superior convergence behavior Index Terms adaptive algorithm blind deconvolution equalizers mobile communica tions quasi Newton algorithm to appear in ELECTRONICS LETTERS Submitted September Accepted October Please address correspondence to Scott C Douglas Department of Electrical Engineering Merrill Engi neering Building University of Utah Salt Lake City UT USA Voice FAX Electronic mail address douglas ee utah edu World Wide Web URL http www elen utah edu douglas