自适应变步长并行Laguerre盲均衡算法研究

Blind Equalization with Adaptive Variable Step Sizes Based on Parallel Laguerre Filter

深衰落信道会引起抽头系数长和误码率高等问题.在分析现有滤波器结构及盲均衡算法的基础上,提出了自适应变步长并行Laguerre盲均衡算法.该算法采用Laguerre序列代替传统抽头延迟,缩短了抽头系数,并借助判决引导算法和分数间隔思想,加快了算法收敛速度.鉴于步长因子对盲均衡器收敛速度、剩余码间干扰影响较大,对不同自适应步长算法进行了分析和比较.在此基础上提出了适用于高速通用数据链信号盲均衡的步长修正方案.实验表明该算法较传统算法在收敛速度、误码性能方面均有所提升.

A blind equalization algorithm with adaptive variable step sizes based on parallel Laguerre filter is proposed to overcome problems such as long tap coefficients, and high bit error rate（BER） caused by deep fading channels. By analyzing existing filter structures and blind equalization algorithms, the proposed algorithm replaces traditional tapped delay with Laguerre sequence to make tap coefficients shorter. Meanwhile, convergence is accelerated by using a decision-directed algorithm and a fractionally spaced structure. Since the step size has a great effect on convergence speed and residual error,different algorithms with variable step sizes are compared. Based on the comparison, a revised equalization algorithm structure is devised to achieve the most suitable step sizes for high-speed common data link（CDL）. Compared with traditional blind equalization algorithms, experimental results show that the proposed method improves equalization performance and reduces BERs remarkably.