Year: 2024
Type: article
Abstract: We propose a channel estimation scheme based on joint sparsity pattern learning (JSPL) for massive multi-input multi-output (MIMO) orthogonal time-frequency-space (OTFS) modulation aided systems. By exploiting the potential joint sparsity of the delay-Doppler-angle (DDA) domain channel, the channel estimation problem is transformed into a sparse recovery problem. To solve it, we first apply thespike and slabprior model to iteratively estimate the support set of the channel matrix, and a higher-accuracy parameter update rule relying on the identified support set is introduced into the iteration. Then the specific values of the channel elements corresponding to the support set are estimated by the orthogonal matching pursuit (OMP) method. Both our simulation results and analysis demonstrate that the proposed JSPL channel estimation scheme achieves an improved performance over the representative state-of-the-art baseline schemes, despite its reduced pilot overhead.
Authors: Kuo Meng, Shaoshi Yang, Xiao-Yang Wang, Yan Bu, Yurong Tang, Jianhua Zhang, Lajos Hanzo
Language: English
Topic: PAPR reduction in OFDM
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
Awards: G108985073, UKRI-India Future Networks Initiative, G1471839284, Pervasive Wireless Intelligence Beyond the Generations (PerCom), G2544329817, Reliable and Robust Quantum Computing, G3401488888, Pervasive Wireless Intelligence Beyond the Generations, Ubiquitous Quantum Communications, G6495392424, G8269789390
OpenAlex ID: W4392576499