Parallel pipelined least-mean-square algorithm and its performance analysis

A novel parallel pipelined least-mean-square algorithm is proposed by introducing parallel processing into the pipelined least-mean-square algorithm. The algorithm presented in this paper has smaller pipelined delay, higher data throughput rate and faster convergence speed, as well as wider step size range in which the convergence behavior of the algorithm is maintained than the pipelined least-mean-square algorithm. It also exhibits some de-correlation effect for the correlated input sequence. These properties make it more suitable for the cases of higher order filter with faster convergence speed. In addition, it can also be used to simplify the hardware implementation of filters.