Optimal Multiuser Detection with Artificial Fish Swarm Algorithm

The optimal multiuser detection for communication systems can be characterized as an NP-hard optimization problem. In this paper, as a new heuristic intelligent optimization algorithm, Artificial Fish Swarm Algorithm (AFSA) is employed for the detection problem, the results show that it has better performances such as good global convergence, strong robustness, insensitive to initial values, simplicity of implementation and faster convergent speed with random initial values compared with genetic algorithm (GA). With the increase of fish or iteration number, the AFSA has only the linear increment of complexity and maintain a superior performance; its improved methods are also proposed and analysed in the end.