摘要
针对无线通信系统中传统常模盲均衡算法(CMA)在脉冲噪声环境下适应性较差,难以有效收敛的问题,提出了基于余弦代价函数的自适应分数低阶盲均衡算法。该算法将改进的余弦代价函数代替分数低阶常模盲均衡算法(FLOSCMA)中的代价函数,不再需要已知原信号的统计模值,其适用性更广。仿真实验结果表明,与Floscma、CMA算法以及其它变步长算法相比,本文算法在收敛速率和稳态误差方面均有所改进。
Due to the large mean square error(MSE) and immerging in partial minimum easily for traditional constant modulus blind equalization algorithm(CMA) under impulse noise environment in wireless communication systems,we presented a new blind equalization algorithm based on improved cosine cost function and variable step-size algorithm.This algorithm replaced the traditional cost function with the improved cosine cost function,which made the algorithm get rid of the statistical model value of original signal.In order to balance the convergence speed and MSE,a new variable step-size algorithm was presented.Simulation results proved that,compared with Floscma、CMA and other variable step algorithm,the new algorithm improved both in convergence rate and MSE.
作者
王旭光
陈红
WANG Xuguang;CHEN Hong(Electronic Countermeasure Institute,National University of Defense Technology,Hefei 230037,China)
出处
《探测与控制学报》
CSCD
北大核心
2019年第1期87-91,共5页
Journal of Detection & Control
关键词
脉冲噪声
盲均衡
余弦代价函数
变步长
impulse noise
blind equalization
cosine cost function
variable step-size algorithm
