{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,17]],"date-time":"2026-02-17T12:13:15Z","timestamp":1771330395349,"version":"3.50.1"},"reference-count":42,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2023,8,14]],"date-time":"2023-08-14T00:00:00Z","timestamp":1691971200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Nature Science Foundation of China","award":["61871239"],"award-info":[{"award-number":["61871239"]}]},{"name":"National Nature Science Foundation of China","award":["61671254"],"award-info":[{"award-number":["61671254"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In the intelligent reflecting surface (IRS)-assisted MIMO systems, optimizing the passive beamforming of the IRS to maximize spectral efficiency is crucial. However, due to the unit-modulus constraint of the IRS, the design of an optimal passive beamforming solution becomes a challenging task. The feature input of existing schemes often neglects to exploit channel state information (CSI), and all input data are treated equally in the network, which cannot effectively pay attention to the key information and features in the input. Also, these schemes usually have high complexity and computational cost. To address these issues, an effective three-channel data input structure is utilized, and an attention mechanism-assisted unsupervised learning scheme is proposed on this basis, which can better exploit CSI. It can also better exploit CSI by increasing the weight of key information in the input data to enhance the expression and generalization ability of the network. The simulation results show that compared with the existing schemes, the proposed scheme can effectively improve the spectrum efficiency, reduce the computational complexity, and converge quickly.<\/jats:p>","DOI":"10.3390\/s23167164","type":"journal-article","created":{"date-parts":[[2023,8,14]],"date-time":"2023-08-14T11:07:10Z","timestamp":1692011230000},"page":"7164","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Passive Beamforming Design of IRS-Assisted MIMO Systems Based on Deep Learning"],"prefix":"10.3390","volume":"23","author":[{"given":"Hui","family":"Zhang","sequence":"first","affiliation":[{"name":"Tianjin Key Laboratory of Optoelectronic Sensor and Sensing Network Technology, Nankai University, Tianjin 300350, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiming","family":"Jia","sequence":"additional","affiliation":[{"name":"Tianjin Key Laboratory of Optoelectronic Sensor and Sensing Network Technology, Nankai University, Tianjin 300350, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Meikun","family":"Li","sequence":"additional","affiliation":[{"name":"Tianjin Key Laboratory of Optoelectronic Sensor and Sensing Network Technology, Nankai University, Tianjin 300350, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingjing","family":"Wang","sequence":"additional","affiliation":[{"name":"Tianjin Key Laboratory of Optoelectronic Sensor and Sensing Network Technology, Nankai University, Tianjin 300350, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuxin","family":"Song","sequence":"additional","affiliation":[{"name":"Tianjin Key Laboratory of Optoelectronic Sensor and Sensing Network Technology, Nankai University, Tianjin 300350, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,8,14]]},"reference":[{"key":"ref_1","unstructured":"(2023, August 03). Cisco Annual Internet Report (2018\u20132023) White Paper. Available online: https:\/\/www.cisco.com\/c\/en\/us\/solutions\/collateral\/executive-perspectives\/annual-internet-report\/white-paper-c11-741490.html?dtid=osscdc000283."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Sylla, T., Mendiboure, L., Maaloul, S., Aniss, H., Chalouf, M.A., and Delbruel, S. (2022). Multi-connectivity for 5G networks and beyond: A survey. Sensors, 22.","DOI":"10.3390\/s22197591"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"4621","DOI":"10.1016\/j.aej.2020.08.020","article-title":"Design and analysis of a 32 \u00d7 5 Gbps passive optical network employing FSO based protection at the distribution level","volume":"59","author":"Mirza","year":"2020","journal-title":"Alex. Eng. J."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"134","DOI":"10.1109\/MNET.001.1900287","article-title":"A vision of 6G wireless systems: Applications, trends, technologies, and open research problems","volume":"34","author":"Saad","year":"2019","journal-title":"IEEE Netw."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1109\/MCOM.001.1900107","article-title":"Towards smart and reconfigurable environment: Intelligent reflecting surface aided wireless network","volume":"58","author":"Wu","year":"2019","journal-title":"IEEE Commun. Mag."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"5394","DOI":"10.1109\/TWC.2019.2936025","article-title":"Intelligent reflecting surface enhanced wireless network via joint active and passive beamforming","volume":"18","author":"Wu","year":"2019","journal-title":"IEEE Trans. Wirel. Commun."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"2746","DOI":"10.1109\/TSP.2018.2816577","article-title":"Beyond massive MIMO: The potential of data transmission with large intelligent surfaces","volume":"66","author":"Hu","year":"2018","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1004","DOI":"10.1049\/iet-com.2010.0544","article-title":"Intelligent walls as autonomous parts of smart indoor environments","volume":"6","author":"Subrt","year":"2012","journal-title":"IET Commun."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1777","DOI":"10.1109\/JSAC.2020.3000822","article-title":"MIMO detection for reconfigurable intelligent surface-assisted millimeter wave systems","volume":"38","author":"Yang","year":"2020","journal-title":"IEEE J. Sel. Areas Commun."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"4157","DOI":"10.1109\/TWC.2019.2922609","article-title":"Reconfigurable intelligent surfaces for energy efficiency in wireless communication","volume":"18","author":"Huang","year":"2019","journal-title":"IEEE Trans. Wirel. Commun."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Jiang, T., and Shi, Y. (2019, January 9\u201313). Over-the-air computation via intelligent reflecting surfaces. Proceedings of the 2019 IEEE Global Communications Conference (GLOBECOM), Waikoloa, HI, USA.","DOI":"10.1109\/GLOBECOM38437.2019.9013643"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"2637","DOI":"10.1109\/JSAC.2020.3007043","article-title":"Robust and secure wireless communications via intelligent reflecting surfaces","volume":"38","author":"Yu","year":"2020","journal-title":"IEEE J. Sel. Areas Commun."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"6367","DOI":"10.1109\/TVT.2022.3160364","article-title":"Reconfigurable intelligent surfaces relying on non-diagonal phase shift matrices","volume":"71","author":"Li","year":"2022","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"3064","DOI":"10.1109\/TWC.2020.2970061","article-title":"Weighted sum-rate maximization for reconfigurable intelligent surface aided wireless networks","volume":"19","author":"Guo","year":"2020","journal-title":"IEEE Trans. Wirel. Commun."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"4522","DOI":"10.1109\/TCOMM.2020.2981458","article-title":"Intelligent reflecting surface meets OFDM: Protocol design and rate maximization","volume":"68","author":"Yang","year":"2020","journal-title":"IEEE Trans. Commun."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Huang, C., Zappone, A., Debbah, M., and Yuen, C. (2018, January 15\u201320). Achievable rate maximization by passive intelligent mirrors. Proceedings of the 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Calgary, AB, Canada.","DOI":"10.1109\/ICASSP.2018.8461496"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"14960","DOI":"10.1109\/TVT.2020.3031657","article-title":"Intelligent reflecting surface-assisted millimeter wave communications: Joint active and passive precoding design","volume":"69","author":"Wang","year":"2020","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1823","DOI":"10.1109\/JSAC.2020.3000814","article-title":"Capacity characterization for intelligent reflecting surface aided MIMO communication","volume":"38","author":"Zhang","year":"2020","journal-title":"IEEE J. Sel. Areas Commun."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Yu, X., Xu, D., and Schober, R. (2019, January 11\u201313). MISO wireless communication systems via intelligent reflecting surfaces. Proceedings of the 2019 IEEE\/CIC International Conference on Communications in China (ICCC), Changchun, China.","DOI":"10.1109\/ICCChina.2019.8855810"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Wu, Q., and Zhang, R. (2018, January 9\u201313). Intelligent reflecting surface enhanced wireless network: Joint active and passive beamforming design. Proceedings of the 2018 IEEE Global Communications Conference (GLOBECOM), Abu Dhabi, United Arab Emirates.","DOI":"10.1109\/GLOCOM.2018.8647620"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1620","DOI":"10.1109\/LWC.2020.2999356","article-title":"Weighted sum-rate maximization for multi-IRS aided cooperative transmission","volume":"9","author":"Li","year":"2020","journal-title":"IEEE Wirel. Commun. Lett."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1931","DOI":"10.1109\/JSAC.2021.3078502","article-title":"Learning to reflect and to beamform for intelligent reflecting surface with implicit channel estimation","volume":"39","author":"Jiang","year":"2021","journal-title":"IEEE J. Sel. Areas Commun."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"694","DOI":"10.1109\/TCCN.2021.3128605","article-title":"A robust deep learning-based beamforming design for RIS-assisted multiuser MISO communications with practical constraints","volume":"8","author":"Xu","year":"2021","journal-title":"IEEE Trans. Cogn. Commun. Netw."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"892","DOI":"10.1109\/LCOMM.2020.3041510","article-title":"Unsupervised learning-based joint active and passive beamforming design for reconfigurable intelligent surfaces aided wireless networks","volume":"25","author":"Song","year":"2020","journal-title":"IEEE Commun. Lett."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"745","DOI":"10.1109\/LWC.2020.2969167","article-title":"Deep reinforcement learning based intelligent reflecting surface optimization for MISO communication systems","volume":"9","author":"Feng","year":"2020","journal-title":"IEEE Wirel. Commun. Lett."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Lee, G., Jung, M., Kasgari, A.T.Z., Saad, W., and Bennis, M. (2020, January 7\u201311). Deep reinforcement learning for energy-efficient networking with reconfigurable intelligent surfaces. Proceedings of the ICC 2020\u20142020 IEEE International Conference on Communications (ICC), Dublin, Ireland.","DOI":"10.1109\/ICC40277.2020.9149380"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1052","DOI":"10.1109\/LCOMM.2020.2965532","article-title":"Unsupervised learning for passive beamforming","volume":"24","author":"Gao","year":"2020","journal-title":"IEEE Commun. Lett."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Taha, A., Alrabeiah, M., and Alkhateeb, A. (2019, January 9\u201313). Deep learning for large intelligent surfaces in millimeter wave and massive MIMO systems. Proceedings of the 2019 IEEE Global Communications Conference (GLOBECOM), Waikoloa, HI, USA.","DOI":"10.1109\/GLOBECOM38437.2019.9013256"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"\u00d6zdo\u011fan, \u00d6., and Bj\u00f6rnson, E. (2020, January 1\u20134). Deep learning-based phase reconfiguration for intelligent reflecting surfaces. Proceedings of the 2020 54th Asilomar Conference on Signals, Systems, and Computers, Virtual.","DOI":"10.1109\/IEEECONF51394.2020.9443516"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Huang, C., Alexandropoulos, G.C., Yuen, C., and Debbah, M. (2019, January 2\u20135). Indoor signal focusing with deep learning designed reconfigurable intelligent surfaces. Proceedings of the 2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Cannes, France.","DOI":"10.1109\/SPAWC.2019.8815412"},{"key":"ref_31","first-page":"836","article-title":"Millimeter wave communications with an intelligent reflector: Performance optimization and distributional reinforcement learning","volume":"21","author":"Zhang","year":"2021","journal-title":"IEEE Trans. Wirel. Commun."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"375","DOI":"10.1109\/TWC.2020.3024860","article-title":"Deep reinforcement learning-based intelligent reflecting surface for secure wireless communications","volume":"20","author":"Yang","year":"2020","journal-title":"IEEE Trans. Wirel. Commun."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1839","DOI":"10.1109\/JSAC.2020.3000835","article-title":"Reconfigurable intelligent surface assisted multiuser MISO systems exploiting deep reinforcement learning","volume":"38","author":"Huang","year":"2020","journal-title":"IEEE J. Sel. Areas Commun."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Ma, D., Li, L., Ren, H., Wang, D., Li, X., and Han, Z. (2020, January 7\u201311). Distributed Rate Optimization for Intelligent Reflecting Surface with Federated Learning. Proceedings of the 2020 IEEE International Conference on Communications Workshops (ICC Workshops), Dublin, Ireland.","DOI":"10.1109\/ICCWorkshops49005.2020.9145388"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Nguyen, N.T., Nguyen, L.V., Huynh-The, T., Nguyen, D.H., Swindlehurst, A.L., and Juntti, M. (2021, January 27\u201330). Machine learning-based reconfigurable intelligent surface-aided MIMO systems. Proceedings of the 2021 IEEE 22nd International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Lucca, Italy.","DOI":"10.1109\/SPAWC51858.2021.9593256"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Guan, X., Wu, Q., and Zhang, R. (2020, January 7\u201311). Anchor-assisted intelligent reflecting surface channel estimation for multiuser communications. Proceedings of the GLOBECOM 2020\u20142020 IEEE Global Communications Conference, Taipei, Taiwan.","DOI":"10.1109\/GLOBECOM42002.2020.9347985"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"7601","DOI":"10.1109\/JIOT.2020.2986442","article-title":"A novel OFDM autoencoder featuring CNN-based channel estimation for internet of vessels","volume":"7","author":"Lin","year":"2020","journal-title":"IEEE Internet Things J."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"871","DOI":"10.1049\/iet-rsn.2018.5438","article-title":"Cognitive radar antenna selection via deep learning","volume":"13","author":"Elbir","year":"2019","journal-title":"IET Radar Sonar Navig."},{"key":"ref_39","unstructured":"Ioffe, S., and Szegedy, C. (2015, January 6\u201311). Batch normalization: Accelerating deep network training by reducing internal covariate shift. Proceedings of the International Conference on Machine Learning, Lille, France."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Hu, J., Shen, L., and Sun, G. (2018, January 18\u201322). Squeeze-and-excitation networks. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA.","DOI":"10.1109\/CVPR.2018.00745"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1109\/LWC.2019.2943466","article-title":"Beamforming design for large-scale antenna arrays using deep learning","volume":"9","author":"Lin","year":"2019","journal-title":"IEEE Wirel. Commun. Lett."},{"key":"ref_42","unstructured":"Kingma, D.P., and Ba, J. (2014). Adam: A method for stochastic optimization. arXiv."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/16\/7164\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T20:33:29Z","timestamp":1760128409000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/16\/7164"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,8,14]]},"references-count":42,"journal-issue":{"issue":"16","published-online":{"date-parts":[[2023,8]]}},"alternative-id":["s23167164"],"URL":"https:\/\/doi.org\/10.3390\/s23167164","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,8,14]]}}}