Blind separation of coherent multipath signals with impulsive interference and Gaussian noise in time-frequency domain.

Blind separation of multipath fading signals with impulsive interference and Gaussian noise is a very challenging issue due to multipath effects, which are often encountered in practical scenarios. Since the strong coherence among multipath signals leads to the extreme superposition in time-frequency (TF) domain, this paper proposes an iterative three-stage blind source separation (ITS-BSS) algorithm for the separation of coherent multipath signals in the presence of impulsive and Gaussian noise. Specifically, an initial estimation of mixing matrix is firstly implemented by some non-TF based algorithms. Secondly, a subspace-based TF-BSS algorithm is developed to determine the number of sources contributing at each auto-source TF point and then reconstruct corresponding sources. Thirdly, the reconstructed sources at current iteration are used to further improve the estimation accuracy of mixing matrix based on the least-squares (LS) algorithm. The last two stages are repeated by iteratively updating mixing matrix and sources until satisfied performance is achieved or a predefined number of iterations is done. Numerical results on multipath phase-shift keying (PSK) and quadrature amplitude modulation (QAM) signals plus impulsive noise under various signal-to-noise ratio (SNR) conditions are provided to demonstrate the feasibility and effectiveness of the proposed ITS-BSS algorithm. (C) 2020 Elsevier B.V. All rights reserved.