Intelligent multi-user detection using an artificial immune system  

作　　者：GONG MaoGuo, JIAO LiCheng, MA WenPing & MA JingJing Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing, Xidian University, Xi’an 710071, China 

出　　处：《Science in China(Series F)》2009年第12期2342-2353,共12页中国科学（F辑英文版）

基　　金：Supported by the National Natural Science Foundation of China (Grant Nos. 60703107, 60703108);the National High-Tech Research & Develop-ment Program of China (Grant No. 2009AA12Z210);the Program for New Century Excellent Talents in University (Grant No. NCET-08-0811);the Program for Cheung Kong Scholars and Innovative Research Team in University (Grant No. IRT-06-45)

摘　　要：Artificial immune systems （AIS） are a kind of new computational intelligence methods which draw inspiration from the human immune system. In this study, we introduce an AIS-based optimization algorithm, called clonal selection algorithm, to solve the multi-user detection problem in code-division multipleaccess communications system based on the maximum-likelihood decision rule. Through proportional cloning, hypermutation, clonal selection and clonal death, the new method performs a greedy search which reproduces individuals and selects their improved maturated progenies after the affinity maturation process. Theoretical analysis indicates that the clonal selection algorithm is suitable for solving the multi-user detection problem. Computer simulations show that the proposed approach outperforms some other approaches including two genetic algorithm-based detectors and the matched filters detector, and has the ability to find the most likely combinations.Artificial immune systems （AIS） are a kind of new computational intelligence methods which draw inspiration from the human immune system. In this study, we introduce an AIS-based optimization algorithm, called clonal selection algorithm, to solve the multi-user detection problem in code-division multipleaccess communications system based on the maximum-likelihood decision rule. Through proportional cloning, hypermutation, clonal selection and clonal death, the new method performs a greedy search which reproduces individuals and selects their improved maturated progenies after the affinity maturation process. Theoretical analysis indicates that the clonal selection algorithm is suitable for solving the multi-user detection problem. Computer simulations show that the proposed approach outperforms some other approaches including two genetic algorithm-based detectors and the matched filters detector, and has the ability to find the most likely combinations.

关 键 词：artificial immune systems clonal selection multi-user detection code-division multiple-access genetic algorithm 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TP277[自动化与计算机技术—控制科学与工程]