Lattice PFBLMS: Fast converging structure for efficient implementation of frequency-domain adaptive filters

Abstract

It has been demonstrated that the unconstrained partitioned fast block LMS (PFBLMS) algorithm suffers from an inherently slow convergence rate. A solution to this problem has previously been proposed by the second author of this paper, which reduces the correlation by reducing the overlap between partitions. A drawback of this solution is that it requires more memory than the conventional PFBLMS algorithm. In this paper, we propose an alternative solution that does not require any additional memory. A lattice structure is used instead to remove the correlation and increase the convergence rate.