Intelligent multi-user detection using an artificial immune system |
| |
Authors: | MaoGuo Gong LiCheng Jiao WenPing Ma JingJing Ma |
| |
Affiliation: | (1) Data Mining and Modeling Capability Corporate R&D, The Dow Chemical Company, 2301 N. Brazosport Blvd., B-1226, Freeport, TX 77541, USA;; |
| |
Abstract: | 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 multiple-access 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. |
| |
Keywords: | artificial immune systems clonal selection multi-user detection code-division multiple-access genetic algorithm |
本文献已被 维普 SpringerLink 等数据库收录! |
|