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

计量
- 文章访问数: 3290
- HTML全文浏览量: 68
- PDF下载量: 709
- 被引次数: 0
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.

HTML全文

参考文献(1)

张铃, 张钹. 佳点集遗传算法[J]. 计算机学报, 2001, 24(9):917-922.Zhang Ling and Zhang Bo. Good point set based geneticalgorithm[J]. Chinese Journal of Computers, 2001, 24(9):917-922.[2]缑水平, 焦李成, 田小林. 基于免疫克隆聚类协同神经网络的图像识别[J].电子与信息学报.2008, 30(2):263-266浏览[3]李阳阳, 焦李成. 求解SAT 问题的量子免疫克隆算法[J]. 计算机学报, 2007, 30(2): 176-183.Li Yang-yang and Jiao Li-cheng. Quantum-inspired immuneclonal algorithm for SAT problem[J]. Chinese Journal ofComputers, 2007, 30(2): 176-183.[4]Soo K K, Siu Y M, Chan W S, Yang L, and Chen R S.Particle-swarm-optimization-based multiuser detector forCDMA communications[J]. IEEE Transactions on VehicularTechnology, 2007, 56(5): 3006-3013.[5]Sharmin M and Tellambura C. Multiuser detection inDS-CDMA using hybrid evolutionary strategy[C]. IEEECanadian Conference on Electrical and ComputerEngineering, Canada, 2008: 605-608.[6]Juang Jih-gau, Huang Ming-te, and Liu Wen-kai. PIDControl using presearched genetic algorithms for a MIMOsystem[J].IEEE Transactions on Systems, Man, andCybernetics-Part C: Applications and Reviews.2008, 38(5):716-727[7]焦李成, 慕彩红, 王伶. 通信中的智能信号处理[M]. 北京: 电子工业出版社, 2006: 209-275.Jiao Li-cheng, Mu Cai-hong, and Wang Ling. Intelligentsignal processing for communications[M]. Beijing: PublishingHouse of Electronics Industry, 2006: 209-275.[8]Mu Cai-hong and Zhu Ming-ming. Clonal selection detectionalgorithm for the V-BLAST system[C][J].Proc. of ICNC 2006,Xian.2006, LNCS 4222:402-411[9]Adjoudani A, Beck E C, and Burg A P, et al.. Prototypeexperience for MIMO BLAST over third-generation wirelesssystem [J].IEEE Journal on Selected Areas inCommunications.2003, 21(3):440-451[10]Golden G D, Foschini C J, Valenzuela R A, and WolnianskyP W. Detection algorithm and initial laboratory results usingV-BLAST space-time communication architecture[J].Electronics Letters.1999, 35(1):14-16[11]Ahn Chang wook and Ramakrishna R S. Elitism-basedcompact genetic algorithms[J].IEEE Transactions onEvolutionary Computation.2003, 7(4):367-385[12]徐宗本, 聂赞坎, 张文修. 父代种群参与竞争遗传算法几乎必然收敛[J]. 应用数学学报, 2002, 25(1): 167-175.Xu Zong-ben, Nie Zan-kan, ang Zhang Wen-xiu. Almost surestrong convergence of a class of genetic algorithms withparent-offsprings competition[J]. Acta MathematicaeApplicatae Sinica, 2002, 25(1): 167-175.

施引文献

资源附件(0)

访问统计