通用数据链并行Laguerre盲均衡算法

Parallel Laguerre blind equalization algorithm for common data link

为解决深衰落信道中传统盲均衡算法存在的长抽头系数和高误码率的问题,提出通用数据链并行Laguerre盲均衡算法。在分析通用数据链信号的基础上,引入Laguerre滤波器替代FIR滤波器,以较短的抽头系数逼近长脉冲序列响应;同时借助判决引导算法和分数间隔思想,加快了算法的收敛速度;利用均衡输出的平方期望直接作为自适应步长模块的修正变量,进一步提升了新算法的均衡性能。实验结果表明,新算法减少了均衡器抽头系数,拥有更快的收敛速度和更低的误码率。

A novel parallel Laguerre blind equalization algorithm for common data link（ CDL） is proposed to overcome the problems of traditional algorithms such as long tap coefficients and the high bit error rate（ BER） for deep fading channels. By analyzing CDL signals,the new algorithm replaces FIR filter with Laguerre filter so as to approach long-pulse response sequence with shorter tap coefficients. Meanwhile,the convergence is accelerated by using the decision-directed algorithm and fractionally spaced structure. The self-adaptive step module directly adopts the expected value from the square of equalized output as a modified variable to further promote its equalization effect. The experimental results show that the proposed method can accelerate convergence and reduce BER in short tap coefficients.