@inproceedings{d75c4977aa224d89b887f4d6e6f56900,
title = "Joint Channel and Impulsive Noise Estimation in Underwater Acoustic MIMO-OFDM Systems Based on Parallel SBL Algorithm",
abstract = "Impulsive noise (IN) can significantly degrade the performance of underwater acoustic communication systems. In this paper, we propose a parallel sparse Bayesian learning (P-SBL) algorithm for joint channel and impulsive noise estimation in underwater acoustic (UWA) multiple-input-multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) systems. The proposed P-SBL algorithm, whose measurement matrix is constructed using a non-orthogonal pilot pattern, can simultaneously estimate the impulsive noise and channel coefficients from multiple transmitters. Simulation results show that the proposed P-SBL algorithm achieves higher channel estimation accuracy and lower system bit-error-rate (BER) compared with existing approaches.",
keywords = "MIMO-OFDM, Underwater acoustic communication, impulsive noise, sparse Bayesian learning",
author = "Zhijiang Liu and Lijun Xu and Qingqing Zhao",
note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; OCEANS 2025 Brest, OCEANS 2025 ; Conference date: 16-06-2025 Through 19-06-2025",
year = "2025",
doi = "10.1109/OCEANS58557.2025.11104703",
language = "English",
series = "Oceans Conference Record (IEEE)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "OCEANS 2025 Brest, OCEANS 2025",
address = "United States",
}