全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...
兵工学报  2015 

基于混合蛙跳算法的多模盲均衡算法

DOI: 10.3969/j.issn.1000-1093.2015.07.017, PP. 1280-1287

Keywords: 信息处理技术,多模算法,混合蛙跳算法,智能优化算法,最优权向量

Full-Text   Cite this paper   Add to My Lib

Abstract:

?针对常模盲均衡算法(CMA)收敛速度慢、收敛后稳态误差大且存在盲相位的现象,提出了一种基于混合蛙跳算法的多模盲均衡算法(SFLA-MMA)。它结合了智能优化算法的基本思想,将个体自身的进化及个体间的社会行为等概念引入到盲均衡技术中。该算法将多模盲均衡算法(MMA)代价函数的倒数定义为混合蛙跳算法(SFLA)的适应度函数,将青蛙群体中青蛙个体的位置向量作为MMA的初始权向量;利用SFLA的全局信息共享机制和局部深度搜索能力,在全局范围内搜索青蛙群体的最优位置向量并作为MMA的初始优化权向量。之后,通过MMA进行迭代,得到MMA的最优权向量。利用高阶多模正交振幅调制(QAM)与正交相移键控(APSK)信号对该算法进行了仿真验证。仿真结果表明,与CMA、MMA和基于粒子群算法的多模盲均衡算法(PSO-MMA)相比,SFLA-MMA在均衡高阶多模信号时收敛速度极快、稳态误差最小、输出信号星座图最清晰。

References

[1]  [1] Yang J, Werner J J, Dumont G A. The multimodulus blind equalization and its generalized algorithm[J]. IEEE Journal on Selected Areas in Communications, 2002, 20(5): 997-1014.
[2]  [4] Java Ebrahimi, Seyed Hossein Hosseinian, Gevorg B Gharehpetian. Unit commitment problem solution using shuffled frog leaping algorithm[J]. IEEE Transactions on Power System, 2011, 26(2): 573-581.
[3]  [5] Amiri B, Fathian M, Maroosi A. Application of shuffled frog-leaping algorithm on clustering[J]. International Journal of Advanced Manufacturing Technology, 2009, 45(1/2): 199-209.
[4]  [6] 骆剑平,李霞,陈泯融. 混合蛙跳算法的Markov模型及其收敛性分析[J]. 电子学报, 2010, 38(12): 2875-2880.
[5]  [7] Eusuff M M, Lansey K E. Optimization of water distribution network design using shuffled frog leaping algorithm[J]. Journal of Water Resources Planning and Management, 2003, 129(3): 210-225.
[6]  [8] 陈 杰,潘峰,王光辉. 粒子群优化算法在动态优化中的研究现状[ J ]. 智能系统学报, 2009, 4(3): 189-198.
[7]  [9] Yao M, Zhang Q T. Diversity reception of DAPSK over generalized fading channels[J]. IEEE Transactions on Wireless Communications, 2005, 4(4): 1834-1845.
[8]  [10] Christian Hager, Alex Alvarado. Design of APSK constellations for coherent optical channels with Nonlinear Phase Noise[J]. IEEE Transactions on Communication, 2013, 61(8): 3362-3373.
[9]  [14] Elbeltagi E, Hegazy T, Grierson D. Comparison among five evolutionary-based optimization algorithm[J]. Advanced Engineering Informatics, 2005, 19(1): 43-53.
[10]  [15] Eusuff M, Lansey K, Pasha F. Shuffled frog leaping algorithm: a memetic meta-heuristic for discrete optimization[J]. Engineering Optimization, 2006, 38(2):129-154
[11]  [2] GAO Yuan, QIU Xin-yun. A new variable step size CMA blind equalization algorithm[C]∥IEEE Chinese Control and Decision Conference. Taiyuan, China: IEEE, 2012: 315-317.
[12]  [3] Jenq-Tay Yuan. Equalization and carrier phase recovery of CMA and MMA in blind adaptive receivers[J]. IEEE Transactions on Signal Processing, 2010, 58(6): 3206-3217.
[13]  [11] 郭业才. 模糊小波神经网络盲均衡理论、算法与实现[M]. 北京:科学出版社,2011: 48-52.
[14]  [12] 段 海滨,张翔银,徐春芳. 仿生智能计算[M]. 北京:科学出版社, 2011: 130-136.
[15]  [13] Li Chang-he, Yang Sheng-xiang. A self-learning particle swarm optimizer for global optimization problems[J]. IEEE Transactions on Systems, 2012, 42(3): 627-646.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133