New Ant Colony Optimization for Optimum Multiuser Detection Problem in DS-CDMA Systems

摘要

This paper presents a new ant colony optimization (ACO) method to solve the optimum multiuser detection (OMD) problem in direct-sequence code-division multiple-access (DS-CDMA) systems. The idea is to use artificial ants to keep track of promising areas of the search space by laying trails of pheromone which guides the search of the ACO, as a heuristic for choosing values to be assigned to variables. An effective local search is performed after each generation of the ACO to improve the quality of solutions. Simulation results show the proposed ACO multiuser detection scheme combined with local search can converge very rapidly to the (near) optimum solutions. The bit error rate (BER) performance of the proposed algorithm is close to the OMD bound for large scale DS-CDMA systems and the computational complexity is polynomial in the number of active users.