Adaptive equalization of CPM signals in a fast flat-fading environment

A new algorithm for adapting the coefficients of an equalizer in a fast flat-fading environment is presented. The cost function to optimize is based on the maximum likelihood sequence estimation (MLSE) index for continuous phase modulated (CPM) data signals. The use of this so-called ML equalizer allows a decrease in the irreducible error rate of the non-equalized receiver, on severe mobile transmission channels. This is important in a personal communications system where the use of inexpensive receive filters is desirable for cost-saving reasons, but also cause a detrimental error rate increase. In the present paper, a corresponding iterative algorithm, fully implementable on a digital signal processor, is presented. This algorithm involves the combination of iterative estimation procedures for QR decomposition, matrix eigenvalue tracking and channel prediction error. The details are presented and simulated performances are discussed.