%0 Journal Article
%T Multiuser Detector Based on Adaptive Artificial Fish School Algorithm<br>基于自适应人工鱼群算法的多用户检测器
%A Yu Yang
%A Yin Zhi-feng
%A Tian Ya-fei
%A <br>俞洋
%A 殷志锋
%A 田亚菲
%J 电子与信息学报
%D 2007
%I 
%X Artificial Fish School Algorithm (AFSA) is a new kind of intelligence optimization algorithm, which has some advantages that Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) do not have. But this algorithm has several disadvantages such as the blindness of searching at the later stage and the poor ability to keep the balance of exploration and exploitation, which reduce its probability of searching the best result. To overcome these problems, two improved AFSA named AAFSA_FP and AAFSA_SP were proposed based on idea of adaptive. Then the new algorithms are applied to solve the multiuser detection problems. Simulation results show that the proposed detectors outperform GA detector and PSO detector in terms of BER, near-far resistant and convergence performance.
%K Multiuser detection
%K Artificial fish school algorithm
%K Intelligence optimization algorithm<br>多用户检测
%K 人工鱼群算法
%K 智能优化法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=1319827C0C74AAE8D654BEA21B7F54D3&jid=EFC0377B03BD8D0EF4BBB548AC5F739A&aid=94D7447E177E23C1&yid=A732AF04DDA03BB3&vid=771469D9D58C34FF&iid=CA4FD0336C81A37A&sid=CDEBD1ACE0A4C1C1&eid=2F56B21F91C9B05B&journal_id=1009-5896&journal_name=电子与信息学报&referenced_num=16&reference_num=6