Stable adaptive channel estimation method under impulsive noise environments

Abstract

SummaryChannel estimation is one of the key technologies for ensuring reliable wireless communications under impulsive noise environments. This paper studies robust adaptive channel estimation methods for mitigating harmful impulsive noises, which are described as alpha‐stable (α‐stable) distribution models. Traditional adaptive channel estimation using the second‐order statistics based least mean square (SOS‐LMS) algorithm does not perform well under α‐stable noise environments, even though it was considered one of attractive approaches for estimating channels in the case of Gaussian noises. Unlike the traditional SOS‐LMS algorithm, in this research, we propose a stable sign‐function‐based LMS algorithm, which can mitigate the impulsive noises. Specifically, we first construct the cost function with minimum ℓ1‐norm error criterion and then derive the updating equation of the proposed algorithm. Compared with the traditional SOS‐LMS, the effectiveness of the proposed algorithm is validated via Monte Carlo simulations in various α‐stable noise scenarios. Copyright © 2015 John Wiley & Sons, Ltd.