Least mean mixed-norm adaptive filtering for impulsive DS-CDMA channels

This paper investigates the performance of using the least mean mixed-norm adaptive algorithm (LMMN) in the adaptation of a non-linear receiver, coupled with a second-order phase tracking subsystem, for asynchronous DS-CDMA communication system impaired by double-spread multipath channel and Gaussian mixture impulsive noise. The nonlinear receiver comprises feed-forward filter (FFF), feedback filter (FBF), and an equalizer/second order phase locked loop (PLL). The investigations study the effect of using various mixing parameter (lambda) and step-size (mu) on the performance of the proposed algorithm in terms of the mean-square error (MSE) and the bit-error-rate (BER). Computer simulation results indicate that the proposed receiver algorithm with lambda equals to 0.9 gives the best performance. Furthermore results show that the best value of the algorithm's step-size is 0.0001. Finally it is demonstrated that non-linear receivers adapted by the proposed algorithm will have faster convergence rate and better BER performance, in comparison with the NLMS adaptive receiver.