@inproceedings{4b6a998bcfd84c76a2001b9f22dad88c,
title = "Exploiting Markov Random Field Sparsity for Wideband Channel Estimation in Massive MIMO Systems",
abstract = "This paper studies the wideband channel estimation (CE) problem in massive multiple-input multiple-output (MIMO) systems employing orthogonal frequency division multiplexing (OFDM). We first develop an angle-delay domain channel model with the sampled steering vectors. Then we propose a Markov random field (MRF) prior to flexibly model the angle-delay domain channel sparsity. The constrained Bethe free energy minimization (CBFEM) framework is introduced to design a message passing algorithm for the CE problem. Finally, simulation results validate the superior performance of our proposed algorithm.",
keywords = "Bethe free energy, Markov random field, Massive MIMO-OFDM, channel estimation, message passing",
author = "Xiaofeng Liu and Wenjin Wang and Xinrui Gong and Xiao Fu and Xiqi Gao and Xia, \{Xiang Gen\}",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 14th IEEE International Conference on Wireless Communications and Signal Processing, WCSP 2022 ; Conference date: 01-11-2022 Through 03-11-2022",
year = "2022",
doi = "10.1109/WCSP55476.2022.10039363",
language = "English",
series = "2022 IEEE 14th International Conference on Wireless Communications and Signal Processing, WCSP 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1040--1045",
booktitle = "2022 IEEE 14th International Conference on Wireless Communications and Signal Processing, WCSP 2022",
address = "United States",
}