Square-root form based derivation of a novel NLMS-like adaptive filtering algorithm

In this paper we derive a new adaptive filtering algorithm. Starting from a general square-root formulation [1], we introduce a normalization transform to the updating scheme of the block-diagonal adaptive algorithm presented in [1]. This algorithm is efficiently implemented with a low complexity, the resulting algorithm is similar to the NLMS one. Simulations, in the context of multichannel adaptive filtering with highly intercorrelated channels, show a fast convergence of our new algorithm.