A novel multiuser detector based on immune clone selection algorithm
Yonggang Wang, Zhuren Feng, Licheng Jiao · 2010
Immune clone selection algorithm (ICSA) and the multi-user detection based on ICSA are studied. Similar to evolutionary algorithms, ICSA is an efficient tool in searching for the global optimum based on the representation of solutions as binary code. It shows better potential capability to solve the optimization problem than evolution algorithm. Two novel multi-user detectors are presented which are basic ICSA multi-user detector and hybrid ICSA multi-user detector with multi-stage detector (ICSA-MSD-MUD). For ICSA-MSD-MUD, the MSD is considered as an operator inside the ICSA algorithm. The hybrid detector can reach excellent performance by utilizing ICSA to implement global search and by utilizing MSD to implement local search. The results of simulation show the feasibility and validity of the presented multi-user detectors.