Intelligent multi-user detection using an artificial immune system

查看全文 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)》索引2009年第52卷第12期,共12页

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. 关键词：人工免疫系统计算智能方法多用户检测克隆选择算法人体免疫系统计算机模拟优化算法决策规则

相关文献

参考文献（17）
引证文献（5）
耦合文献（9）

参考文献(17)

引证文献(5)

耦合文献(9)

互联网出版许可证新出网证(渝)字10号全国400电话 - 免长途话费

Intelligent multi-user detection using an artificial immune system

参考文献(17)

引证文献(5)

耦合文献(9)

用户提示