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Based on the assumption of Gaussian noise model, conventional adaptivefiltering algorithms for reconstruction sparse channels were proposed to takeadvantage of channel sparsity due to the fact that broadband wireless channelsusually have the sparse nature. However, state-of-the-art algorithms arevulnerable to deteriorate under the assumption of non-Gaussian noise models(e.g., impulsive noise) which often exist in many advanced communicationssystems. In this paper, we study the problem of RObust Sparse Adaptive channelestimation (ROSA) in the environment of impulsive noises using variablestep-size affine projection sign algorithm (VSS-APSA). Specifically, standardVSS-APSA algorithm is briefly reviewed and three sparse VSS-APSA algorithms areproposed to take advantage of channel sparsity with different sparseconstraints. To fairly evaluate the performance of these proposed algorithms,alpha-stable noise is considered to approximately model the realistic impulsivenoise environments. Simulation results show that the proposed algorithms canachieve better performance than standard VSS-APSA algorithm in differentimpulsive environments.

ROSA: Robust sparse adaptive channel estimation in the presence of impulsive noises