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Intelligent multi-user detection using an artificial immune system 被引量:5

Intelligent multi-user detection using an artificial immune system
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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.
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)
关键词 artificial immune systems clonal selection multi-user detection code-division multiple-access genetic algorithm artificial immune systems, clonal selection, multi-user detection, code-division multiple-access, genetic algorithm
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