{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T02:11:05Z","timestamp":1771467065221,"version":"3.50.1"},"reference-count":39,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2024,9,14]],"date-time":"2024-09-14T00:00:00Z","timestamp":1726272000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>For the deployment of Sixth Generation (6G) networks, integrating Massive Multiple-Input Multiple-Output (Massive MIMO) systems with Intelligent Reflecting Surfaces (IRS) is highly recommended due to its significant benefits in reducing communication losses for Non-Line-of-Sight (NLoS) conditions. However, the use of passive IRS presents challenges in channel estimation, mainly due to the significant feedback overhead required in Frequency Division Duplex (FDD)-based Massive MIMO systems. To address these challenges, this paper introduces a novel Denoising Gated Recurrent Unit with a Dropout-based Channel state information Network (DGD-CNet). The proposed DGD-CNet model is specifically designed for FDD-based IRS-aided Massive MIMO systems, aiming to reduce the feedback overhead while improving the channel estimation accuracy. By leveraging the Dropout (DO) technique with the Gated Recurrent Unit (GRU), the DGD-CNet model enhances the channel estimation accuracy and effectively captures both spatial structures and time correlation in time-varying channels. The results show that the proposed DGD-CNet model outperformed existing models in the literature, achieving at least a 26% improvement in Normalized Mean Square Error (NMSE), a 2% increase in correlation coefficient, and a 4% in system accuracy under Low-Compression Ratio (Low-CR) in indoor situations. Additionally, the proposed model demonstrates effectiveness across different CRs and in outdoor scenarios.<\/jats:p>","DOI":"10.3390\/s24185977","type":"journal-article","created":{"date-parts":[[2024,9,16]],"date-time":"2024-09-16T11:36:37Z","timestamp":1726486597000},"page":"5977","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["DGD-CNet: Denoising Gated Recurrent Unit with a Dropout-Based CSI Network for IRS-Aided Massive MIMO Systems"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0583-5141","authenticated-orcid":false,"given":"Amina","family":"Abdelmaksoud","sequence":"first","affiliation":[{"name":"Electronics and Communications Department, Faculty of Engineering, Modern Academy for Engineering and Technology, Cairo 11585, Egypt"},{"name":"Electronics and Communications Department, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2375-2494","authenticated-orcid":false,"given":"Bassant","family":"Abdelhamid","sequence":"additional","affiliation":[{"name":"Electronics and Communications Department, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9445-2782","authenticated-orcid":false,"given":"Hesham","family":"Elbadawy","sequence":"additional","affiliation":[{"name":"Network Planning Department, National Telecommunication Institute, Cairo 11768, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5291-0212","authenticated-orcid":false,"given":"Hadia","family":"El Hennawy","sequence":"additional","affiliation":[{"name":"Electronics and Communications Department, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4267-8672","authenticated-orcid":false,"given":"Sherif","family":"Eldyasti","sequence":"additional","affiliation":[{"name":"Electronics and Communications Department, Arab Academy for Science, Technology and Maritime Transport, Cairo 11799, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,9,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"10754","DOI":"10.1109\/TVT.2022.3187656","article-title":"Joint Spatial Division and Multiplexing for FDD in Intelligent Reflecting Surface-Assisted Massive MIMO Systems","volume":"71","author":"Papazafeiropoulos","year":"2022","journal-title":"IEEE Trans. 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