M-精英进化算法及其在V-BLAST系统中的应用

慕彩红; 焦李成; 刘逸

doi:10.3724/SP.J.1146.2008.01328

M-精英进化算法及其在V-BLAST系统中的应用

doi: 10.3724/SP.J.1146.2008.01328

慕彩红^{①;焦李成},
焦李成,
刘逸

基金项目:

国家自然科学基金(60703107，60703108，60703109，60702062)，国家863计划项目(2006AA01Z107，2007AA12Z136，2007AA12Z223)，国家973规划项目(2006CB705700)和教育部长江学者和创新团队支持计划(IRT0645)资助课题

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出版历程
- 收稿日期: 2008-10-14
- 修回日期: 2009-06-01
- 刊出日期: 2009-10-19

M-elitist Evolutionary Algorithm and Its Application to V-BLAST System

Mu Cai-hong^{①;焦李成},
Jiao Li-cheng,
Liu Yi

摘要

摘要: 为解决垂直分层空时(V-BLAST)系统中的最大似然检测算法(ML)复杂度过高的问题，并针对通信系统对实时性要求较高的特点，该文提出了一种复杂度较低且性能优良的进化算法，即M-精英进化算法(MEA)，来逼近ML检测算法。通过一个经典背包问题的仿真验证了MEA求解组合优化问题的有效性，实际的通信系统仿真表明,基于MEA的检测算法优于一些经典的检测算法，也优于基于标准遗传算法及克隆选择算法的检测算法，能够较好地逼近ML检测算法。
- 通信系统; 进化算法; 垂直分层空时系统; 背包问题; 最大似然检测算法; M-精英
Abstract: A new algorithm named as M-elitist Evolutionary Algorithm (MEA) is presented with low complexity and high performance to approach the performance of Maximum-Likelihood(ML) detection, for solving the problem of the high complexity of ML detection in real-time Vertical- Bell laboratories LAyered Space-Time (V-BLAST) communication system. The simulation of one knapsack problem validates the effectiveness of MEA to solve combinatorial optimization problems. Furthermore, the simulation of V-BLAST communication system shows that the MEA-based detection algorithm can approach the performance of ML well, and is superior to the detection algorithm based on standard genetic algorithm and that based on clonal selection algorithm as well as some classical ones.

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