{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:42:24Z","timestamp":1760150544614,"version":"build-2065373602"},"reference-count":31,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2023,11,29]],"date-time":"2023-11-29T00:00:00Z","timestamp":1701216000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Fundamental Research Funds for the Central Universities"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Wireless broadband transmission channels usually have time-domain-sparse properties, and the reconstruction of these channels using a greedy search-based orthogonal matching pursuit (OMP) algorithm can effectively improve channel estimation performance while decreasing the length of the reference signal. In this research, the improved OMP and SOMP algorithms for compressed-sensing (CS)-based channel estimation are proposed for single-carrier frequency domain equalization (SC-FDE) systems, which, in comparison with conventional algorithms, calculate the path gain after obtaining the path delay and updating the observation matrices. The reliability of the communication system is further enhanced because the channel path gain is calculated using longer observation vectors, which lowers the Cram\u00e9r\u2013Rao lower bound (CRLB) and results in better channel estimation performance. The developed method can also be applied to time-domain-synchronous OFDM (TDS-OFDM) systems, and it is applicable to the improvement of other matching pursuit algorithms.<\/jats:p>","DOI":"10.3390\/s23239509","type":"journal-article","created":{"date-parts":[[2023,11,30]],"date-time":"2023-11-30T00:34:10Z","timestamp":1701304450000},"page":"9509","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["An Improved Orthogonal Matching Pursuit Algorithm for CS-Based Channel Estimation"],"prefix":"10.3390","volume":"23","author":[{"given":"Lu","family":"Si","sequence":"first","affiliation":[{"name":"State Key Laboratory of Media Convergence & Communication, Communication University of China, Beijing 100024, China"},{"name":"Engineering Research Center of Digital Audio & Video, Ministry of Education, Communication University of China, Beijing 100024, China"}]},{"given":"Weizhang","family":"Xu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Media Convergence & Communication, Communication University of China, Beijing 100024, China"},{"name":"Engineering Research Center of Digital Audio & Video, Ministry of Education, Communication University of China, Beijing 100024, China"}]},{"given":"Xinle","family":"Yu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Media Convergence & Communication, Communication University of China, Beijing 100024, China"},{"name":"Engineering Research Center of Digital Audio & Video, Ministry of Education, Communication University of China, Beijing 100024, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0889-3902","authenticated-orcid":false,"given":"Hang","family":"Yin","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Media Convergence & Communication, Communication University of China, Beijing 100024, China"},{"name":"Engineering Research Center of Digital Audio & Video, Ministry of Education, Communication University of China, Beijing 100024, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,11,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1058","DOI":"10.1109\/JPROC.2010.2042415","article-title":"Compressed channel sensing: A new approach to estimating sparse multipath channels","volume":"98","author":"Bajwa","year":"2010","journal-title":"Proc. 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