{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:37:37Z","timestamp":1760143057170,"version":"build-2065373602"},"reference-count":43,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2024,1,8]],"date-time":"2024-01-08T00:00:00Z","timestamp":1704672000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62201388","62201389","22ZR1463400","2022-5-YB-01"],"award-info":[{"award-number":["62201388","62201389","22ZR1463400","2022-5-YB-01"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Natural Science Foundation of Shanghai","award":["62201388","62201389","22ZR1463400","2022-5-YB-01"],"award-info":[{"award-number":["62201388","62201389","22ZR1463400","2022-5-YB-01"]}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["62201388","62201389","22ZR1463400","2022-5-YB-01"],"award-info":[{"award-number":["62201388","62201389","22ZR1463400","2022-5-YB-01"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Attaining precise target detection and channel measurements are critical for guiding beamforming optimization and data demodulation in massive multiple-input multiple-output (MIMO) communication systems with hybrid structures, which requires large pilot overhead as well as substantial computational complexity. With benefits from the powerful detection characteristics of MIMO radar, we aim for designing a novel sensing-assisted semi-blind detection scheme in this paper, where both the inherent low-rankness of signal matrix and the essential knowledge about geometric environments are fully exploited under a designated cooperative manner. Specifically, to efficiently recover the channel factorizations via the formulated low-rank matrix completion problem, a low-complexity iterative algorithm stemming from the alternating steepest descent (ASD) method is adopted to obtain the solutions in case of unknown noise statistics. Moreover, we take one step forward by employing the denoising convolutional neural network (DnCNN) to preprocess the received signals due to its favorable performance of handling Gaussian denoising. The overall paradigm of our proposed scheme consists of three stages, namely (1) target parameter sensing, (2) communication signal denoising and (3) semi-blind detection refinement. Simulation results show that significant estimation gains can be achieved by the proposed scheme with reduced training overhead in a variety of system settings.<\/jats:p>","DOI":"10.3390\/rs16020247","type":"journal-article","created":{"date-parts":[[2024,1,8]],"date-time":"2024-01-08T07:59:20Z","timestamp":1704700760000},"page":"247","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Sensing and Deep CNN-Assisted Semi-Blind Detection for Multi-User Massive MIMO Communications"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5021-3686","authenticated-orcid":false,"given":"Fengxia","family":"Han","sequence":"first","affiliation":[{"name":"School of Software Engineering, Tongji University, Shanghai 201804, China"},{"name":"Engineering Research Center of Key Software Technologies for Smart City Perception and Planning, Ministry of Education, Shanghai 200003, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0180-7733","authenticated-orcid":false,"given":"Jin","family":"Zeng","sequence":"additional","affiliation":[{"name":"School of Software Engineering, Tongji University, Shanghai 201804, China"}]},{"given":"Le","family":"Zheng","sequence":"additional","affiliation":[{"name":"School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China"},{"name":"Beijing Institute of Technology Chongqing Innovation Center, Chongqing 401120, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6133-693X","authenticated-orcid":false,"given":"Hongming","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China"}]},{"given":"Jianhui","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Electronic and Information Engineering, Tongji University, Shanghai 201804, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,1,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"140","DOI":"10.1109\/MWC.006.2100543","article-title":"Nine challenges in artificial intelligence and wireless communications for 6G","volume":"29","author":"Tong","year":"2022","journal-title":"IEEE Wirel. 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