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Stable adaptive channel estimation method under impulsive noise environments
Author(s) -
Gui Guan,
Zhang Tingping,
Dan Jingpei,
Xu Li
Publication year - 2017
Publication title -
international journal of communication systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.344
H-Index - 49
eISSN - 1099-1131
pISSN - 1074-5351
DOI - 10.1002/dac.3104
Subject(s) - computer science , least mean squares filter , noise (video) , channel (broadcasting) , algorithm , gaussian noise , wireless , key (lock) , adaptive filter , telecommunications , artificial intelligence , image (mathematics) , computer security
Summary Channel 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 ℓ 1 ‐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.