Multi-user Detection Based on Tabu Simulated Annealing Genetic Algorithm

To design an optimal multiuse detector of low complexity and resolve local convergent problem, a hybrid approach that employs a genetic algorithm (GA) and a simulated annealing (SA) and a tabu search (TS) for multi-user detection problem in Code Division Multiple Access (CDMA) communications system is proposed. Using this approach, a genetic algorithm is used to provide a good initial value of tabu search, because the initial value is very important for the performance of a tabu search. Additionally, we apply simulated annealing (SA) to GA and design self-adaptation crossover probability and mutation probability according to simulated annealing ideas. Using this method can make the new detector avoid local optimum and gradually convergent to the feasible globally optimal solution. We called the new detector tabu simulate annealing genetic algorithm (TSAGA). Simulation results for the synchronous case are provided to show that the proposed TSAGA detector has significant performance improvements over the conventional detectors.