Adaptive robust detection for CDMA using a genetic algorithm

Abstract

A novel adaptive robust multi-user detector for code-division multiple access (CDMA) using a real-coded genetic algorithm (GA) is proposed. The GA implicitly implements Huber's M-estimator and is robust against heavy-tailed impulsive noise. The novel feature of this GA-based detector lies in joint symbol detection and adaptive estimation of the cut-off parameter of the M-estimator's object function through a GA optimisation strategy. In particular, the GA-based detector carries out a multipoint search by manipulating and maintaining a population of candidate solutions for different values of the cut-off parameter to encourage information formation and exchange. Since the GA treats the cut-off parameter as one of its optimisation parameters, the need for a separate channel estimator is thus eliminated. Simulation results are provided to examine the evolutionary behaviour and the detection performance of the proposed GA-based detector. It is shown that the GA approach provides good adaptive impulsive noise rejection capability.