量子人工鱼群优化的自适应最小熵盲均衡算法

系统仿真学报 ›› 2016, Vol. 28 ›› Issue (2): 449-454.

量子人工鱼群优化的自适应最小熵盲均衡算法

郭业才^1,2, 吴星¹, 黄伟³, 王惠²

1.南京信息工程大学江苏省气象探测与信息处理重点实验室,江苏南京 210044;
2.南京信息工程大学江苏省大气环境与装备技术协同创新中心,江苏南京 210044;
3.安徽理工大学电气与信息工程学院,安徽淮南 232001

收稿日期:2014-09-28 修回日期:2015-01-01 出版日期:2016-02-08 发布日期:2020-08-17
作者简介:郭业才(1962-),男,安徽,博士,教授,博导,研究方向为水声信号处理,通信信号处理,自适应盲均衡技术。
基金资助:
江苏省高校科研成果产业化推进项目(JHB2012-9); 江苏省高校自然科学研究重大项目(13KJA510001)

Adaptive Minimum Entropy Blind Equalization Algorithm Based on Quantum Artificial Fish Swarm Optimization

Guo Yecai^1,2, Wu Xing¹, Huang Wei³, Wang Hui²

1. Jiangsu Key Laboratory of Meteorological Observation and Information Processing, Nanjing University of Information Science & Technology, Nanjing 210044, China;
2. Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment, Nanjing University of Information Science & Technology, Nanjing 210044, China;
3. School of Electrical & Information Engineering, Anhui University of Science & Technology, Huainan 232001, China;

Received:2014-09-28 Revised:2015-01-01 Online:2016-02-08 Published:2020-08-17

摘要/Abstract

摘要： 为提高高阶非常模信号的均衡效果,提出了量子人工鱼群优化的自适应最小熵盲均衡算法。该算法利用超指数迭代加快了自适应最小熵盲均衡算法的收敛速度;利用薛定谔方程设计量子粒子群模型的思想,设计了快速全局寻优能力的量子人工鱼群模型,减小了超指数自适应最小熵盲均衡算法的稳态误差。仿真结果表明：与自适应最小熵盲均衡算法、超指数自适应最小熵盲均衡算法相比,量子人工鱼群优化的自适应最小熵盲均衡算法收敛速度快、稳态误差小,有利于提高通信质量。

关键词: 盲均衡算法, 幅度相位频移键控, 收敛速度, 量子人工鱼群

Abstract: In order to improve the equalization performance of high order inconstant modulus signals, adaptive minimum entropy super-exponential iteration blind equalization algorithm based on quantum artificial fish swarm optimization was proposed. The proposed algorithm could accelerate convergence rate via super-exponential iteration algorithm and could further decease the mean square error of the super-exponential iteration adaptive minimum entropy blind equalization algorithm via using the global optimization of the quantum artificial fish swarm algorithm designed by Schrodinger equation. The simulation results demonstrate that the proposed algorithm has fast convergence rate and lower mean square error for different higher modulation signals comparison with adaptive minimum entropy blind equalization algorithm and super-exponential iteration adaptive minimum entropy blind equalization algorithm.

Key words: blind equalization algorithm, amplitude phase shift key, convergence rate, quantum artificial fish swarm

中图分类号:

TN911.7

郭业才, 吴星, 黄伟, 王惠. 量子人工鱼群优化的自适应最小熵盲均衡算法[J]. 系统仿真学报, 2016, 28(2): 449-454.

Guo Yecai, Wu Xing, Huang Wei, Wang Hui. Adaptive Minimum Entropy Blind Equalization Algorithm Based on Quantum Artificial Fish Swarm Optimization[J]. Journal of System Simulation, 2016, 28(2): 449-454.

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