A Multiuser Detection Based on Multi-Objectives Optimization-Genetic Algorithm

A multiuser detection based on multi-objective optimization-genetic algorithm (MOO-GA) is proposed for the space-time block coded-multicarrier code-division multiple-access (STBC-MC-CDMA) systems. Due to the spatial diversity, the signals received at the different antennas are faded independently, resulting in an independent log-likelihood function (LLF) for each antenna. To resolve the multi-objective dilemma when choosing one signal estimation for multiple receive-antenna-branches, the proposed MOO-GA selects a subset of the Pareto Front for further evolution. By getting rid of the sub-optimal in terms of multi-objectives, the MOO-GA enhances the evolution probability of the optimal in terms of each single objective. The analysis and simulation shows that the proposed scheme has lower bit-error-rate and less computational complexity.