{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T16:41:37Z","timestamp":1783701697903,"version":"3.55.0"},"reference-count":56,"publisher":"American Association for the Advancement of Science (AAAS)","content-domain":{"domain":["spj.science.org"],"crossmark-restriction":true},"short-container-title":["Intell Comput"],"published-print":{"date-parts":[[2024,1]]},"abstract":"<jats:p>The reconfigurable intelligent surface (RIS) is a promising technology for terahertz (THz) massive multiple-input multiple-output (MIMO) communication systems. However, acquiring high-dimensional channel state information (CSI) and realizing efficient active\/passive beamforming for RIS are challenging owing to its cascaded channel structure and lack of signal processing units. To overcome these challenges, this study proposes a deep learning (DL)-based physical signal processing scheme for RIS-aided THz massive MIMO systems over hybrid far-near field channels wherein channel estimation with low pilot overhead and robust beamforming are implemented. Specifically, first, an end-to-end DL-based channel estimation framework that consists of pilot design, CSI feedback, subchannel estimation, and channel extrapolation is introduced. In this framework, only some RIS elements are first activated, a subsampling RIS channel is then estimated, and a DL-based extrapolation network is finally used to reconstruct the full-dimensional CSI. Next, to maximize the sum rate under imperfect CSI, a DL-based scheme is developed to simultaneously design hybrid active beamforming at the base station and passive beamforming at the RIS. Simulation results show that the proposed channel extrapolation scheme achieves better CSI reconstruction performance than conventional schemes while greatly reducing pilot overhead. Moreover, the proposed beamforming scheme outperforms conventional schemes in terms of robustness to imperfect CSI.<\/jats:p>","DOI":"10.34133\/icomputing.0065","type":"journal-article","created":{"date-parts":[[2023,12,20]],"date-time":"2023-12-20T07:40:01Z","timestamp":1703058001000},"update-policy":"https:\/\/doi.org\/10.34133\/aaas_crossmark_01","source":"Crossref","is-referenced-by-count":7,"title":["Deep Learning\u2013Based Channel Extrapolation and Multiuser Beamforming for RIS-aided Terahertz Massive MIMO Systems over Hybrid-Field Channels"],"prefix":"10.34133","volume":"3","author":[{"given":"Yang","family":"Wang","sequence":"first","affiliation":[{"name":"MIIT Key Laboratory of Complex-Field Intelligent Sensing, Beijing Institute of Technology, Beijing, China."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhen","family":"Gao","sequence":"additional","affiliation":[{"name":"MIIT Key Laboratory of Complex-Field Intelligent Sensing, Beijing Institute of Technology, Beijing, China."},{"name":"Yangtze Delta Region Academy of Beijing Institute of Technology, Beijing Institute of Technology, Jiaxing, China."},{"name":"Advanced Research Institute of Multidisciplinary Science, Beijing Institute of Technology, Jinan, China."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sheng","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Electronics and Computer Science, University of Southampton, Southampton, UK."},{"name":"Faculty of Information Science and Engineering, Ocean University of China, Qingdao, China."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chun","family":"Hu","sequence":"additional","affiliation":[{"name":"MIIT Key Laboratory of Complex-Field Intelligent Sensing, Beijing Institute of Technology, Beijing, China."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dezhi","family":"Zheng","sequence":"additional","affiliation":[{"name":"MIIT Key Laboratory of Complex-Field Intelligent Sensing, Beijing Institute of Technology, Beijing, China."}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"221","published-online":{"date-parts":[[2024,3,13]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/OJCOMS.2019.2953633","article-title":"Terahertz band: The last piece of RF spectrum puzzle for communication systems","volume":"1","author":"Elayan H","year":"2020","unstructured":"Elayan H, Amin O, Shihada B, Shubair RM, Alouini M-S. Terahertz band: The last piece of RF spectrum puzzle for communication systems. IEEE Open J Commun Soc. 2020;1:1\u201332.","journal-title":"IEEE Open J Commun Soc"},{"issue":"6","key":"e_1_3_3_3_2","doi-asserted-by":"crossref","first-page":"3097","DOI":"10.1109\/TWC.2015.2401560","article-title":"Indoor Terahertz communications: How many antenna arrays are needed?","volume":"14","author":"Lin C","year":"2015","unstructured":"Lin C, Li GY. Indoor Terahertz communications: How many antenna arrays are needed? IEEE Trans Wirel Commun. 2015;14(6):3097\u20133107.","journal-title":"IEEE Trans Wirel Commun"},{"issue":"3","key":"e_1_3_3_4_2","first-page":"501","article-title":"Hybrid digital and analog beamforming design for large-scale antenna arrays","volume":"10","author":"Sohrabi F","year":"2016","unstructured":"Sohrabi F, Yu W. Hybrid digital and analog beamforming design for large-scale antenna arrays. IEEE Open J Commun Soc. 2016;10(3):501\u2013513.","journal-title":"IEEE Open J Commun Soc"},{"key":"e_1_3_3_5_2","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2020.3007211"},{"issue":"5","key":"e_1_3_3_6_2","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1109\/MWC.001.1900534","article-title":"Holographic mimo surfaces for 6g wireless networks: Opportunities, challenges, and trends","volume":"27","author":"Huang C","year":"2020","unstructured":"Huang C, Hu S, Alexandropoulos GC, Zappone A, Yuen C, Zhang R, Di Renzo M, Debbah M. Holographic mimo surfaces for 6g wireless networks: Opportunities, challenges, and trends. IEEE Wirel Commun. 2020;27(5):118\u2013125.","journal-title":"IEEE Wirel Commun"},{"issue":"1","key":"e_1_3_3_7_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13638-019-1438-9","article-title":"Smart radio environments empowered by reconfigurable ai meta-surfaces: An idea whose time has come","volume":"2019","author":"Renzo MD","year":"2019","unstructured":"Renzo MD, Debbah M, Phan-Huy D-T, Zappone A, Alouini M-S, Yuen C, Sciancalepore V, Alexandropoulos GC, Hoydis J, Gacanin H, et al. Smart radio environments empowered by reconfigurable ai meta-surfaces: An idea whose time has come. EURASIP J Wirel Commun Netw. 2019;2019(1):1\u201320.","journal-title":"EURASIP J Wirel Commun Netw"},{"issue":"8","key":"e_1_3_3_8_2","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 C","year":"2019","unstructured":"Huang C, Zappone A, Alexandropoulos GC, Debbah M, Yuen C. Reconfigurable intelligent surfaces for energy efficiency in wireless communication. IEEE Trans Wirel Commun. 2019;18(8):4157\u20134170.","journal-title":"IEEE Trans Wirel Commun"},{"issue":"9","key":"e_1_3_3_9_2","doi-asserted-by":"crossref","first-page":"1494","DOI":"10.1109\/JPROC.2022.3174030","article-title":"Pervasive machine learning for smart radio environments enabled by reconfigurable intelligent surfaces","volume":"110","author":"Alexandropoulos GC","year":"2022","unstructured":"Alexandropoulos GC, Stylianopoulos K, Huang C, Yuen C, Bennis M, Debbah M. Pervasive machine learning for smart radio environments enabled by reconfigurable intelligent surfaces. Proc IEEE. 2022;110(9):1494\u20131525.","journal-title":"Proc IEEE"},{"issue":"5","key":"e_1_3_3_10_2","doi-asserted-by":"crossref","first-page":"1431","DOI":"10.1109\/JSAC.2023.3240781","article-title":"Deep learning-based rate-splitting multiple access for reconfigurable intelligent surface-aided tera-hertz massive mimo","volume":"41","author":"Wu M","year":"2023","unstructured":"Wu M, Gao Z, Huang Y, Xiao Z, Ng DWK, Zhang Z. Deep learning-based rate-splitting multiple access for reconfigurable intelligent surface-aided tera-hertz massive mimo. IEEE J Sel Areas Commun. 2023;41(5):1431\u20131451.","journal-title":"IEEE J Sel Areas Commun"},{"issue":"4","key":"e_1_3_3_11_2","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1109\/MAP.2017.2706648","article-title":"Fraunhofer and fresnel distances: Unified derivation for aperture antennas","volume":"59","author":"Selvan KT","year":"2017","unstructured":"Selvan KT, Janaswamy R. Fraunhofer and fresnel distances: Unified derivation for aperture antennas. IEEE Antennas Propag Mag. 2017;59(4):12\u201315.","journal-title":"IEEE Antennas Propag Mag"},{"issue":"4","key":"e_1_3_3_12_2","doi-asserted-by":"crossref","first-page":"2663","DOI":"10.1109\/TCOMM.2022.3146400","article-title":"Channel estimation for extremely large-scale MIMO: Far-field or near-field?","volume":"70","author":"Cui M","year":"2022","unstructured":"Cui M, Dai L. Channel estimation for extremely large-scale MIMO: Far-field or near-field? IEEE Trans Commun. 2022;70(4):2663\u20132677.","journal-title":"IEEE Trans Commun"},{"issue":"2","key":"e_1_3_3_13_2","doi-asserted-by":"crossref","first-page":"1391","DOI":"10.1109\/TCOMM.2021.3138791","article-title":"Joint inter-path and intra-path multiplexing for Terahertz widely-spaced multi-subarray hybrid beamforming systems","volume":"70","author":"Yan L","year":"2022","unstructured":"Yan L, Chen Y, Han C, Yuan J. Joint inter-path and intra-path multiplexing for Terahertz widely-spaced multi-subarray hybrid beamforming systems. IEEE Trans Commun. 2022;70(2):1391\u20131406.","journal-title":"IEEE Trans Commun"},{"key":"e_1_3_3_14_2","doi-asserted-by":"crossref","unstructured":"Mishra D Johansson H. Channel estimation and low-complexity beamforming design for passive intelligent surface assisted miso wireless energy transfer. Paper presented at: ICASSP 2019 - 2019 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP); 2019 May 12\u201317; Brighton UK.","DOI":"10.1109\/ICASSP.2019.8683663"},{"key":"e_1_3_3_15_2","doi-asserted-by":"crossref","first-page":"905","DOI":"10.1109\/LSP.2020.2998357","article-title":"Compressed channel estimation for intelligent reflecting surface-assisted millimeter wave systems","volume":"27","author":"Wang P","year":"2020","unstructured":"Wang P, Fang J, Duan H, Li H. Compressed channel estimation for intelligent reflecting surface-assisted millimeter wave systems. IEEE Signal Process Lett. 2020;27:905\u2013909.","journal-title":"IEEE Signal Process Lett"},{"issue":"6","key":"e_1_3_3_16_2","doi-asserted-by":"crossref","first-page":"4144","DOI":"10.1109\/TCOMM.2021.3063236","article-title":"Channel estimation for RIS-empowered multi-user MISO wireless communications","volume":"69","author":"Wei L","year":"2021","unstructured":"Wei L, Huang C, Alexandropoulos GC, Yuen C, Zhang Z, Debbah M. Channel estimation for RIS-empowered multi-user MISO wireless communications. IEEE Trans Commun. 2021;69(6):4144\u20134157.","journal-title":"IEEE Trans Commun"},{"issue":"9","key":"e_1_3_3_17_2","doi-asserted-by":"crossref","first-page":"1447","DOI":"10.1109\/LWC.2020.2993699","article-title":"Deep channel learning for large intelligent surfaces aided mm-wave massive MIMO systems","volume":"9","author":"Elbir AM","year":"2020","unstructured":"Elbir AM, Papazafeiropoulos A, Kourtessis P, Chatzinotas S. Deep channel learning for large intelligent surfaces aided mm-wave massive MIMO systems. IEEE Wirel Commun Lett. 2020;9(9):1447\u20131451.","journal-title":"IEEE Wirel Commun Lett"},{"issue":"8","key":"e_1_3_3_18_2","doi-asserted-by":"crossref","first-page":"9223","DOI":"10.1109\/TVT.2020.3005402","article-title":"Deep denoising neural network assisted compressive channel estimation for mmwave intelligent reflecting surfaces","volume":"69","author":"Liu S","year":"2020","unstructured":"Liu S, Gao Z, Zhang J, Renzo MD, Alouini M-S. Deep denoising neural network assisted compressive channel estimation for mmwave intelligent reflecting surfaces. IEEE Trans Veh Technol. 2020;69(8):9223\u20139228.","journal-title":"IEEE Trans Veh Technol"},{"key":"e_1_3_3_19_2","first-page":"1","article-title":"Codebook-based solutions for reconfigurable intelligent surfaces and their open challenges","author":"An J","year":"2022","unstructured":"An J, Xu C, Wu Q, Ng DWK, Di Renzo M, Yuen C, Hanzo L. Codebook-based solutions for reconfigurable intelligent surfaces and their open challenges. IEEE Wirel Commun. 2022;1\u20138.","journal-title":"IEEE Wirel Commun"},{"issue":"7","key":"e_1_3_3_20_2","doi-asserted-by":"crossref","first-page":"4640","DOI":"10.1109\/TCOMM.2022.3179771","article-title":"Joint channel estimation and signal recovery for ris-empowered multiuser communications","volume":"70","author":"Wei L","year":"2022","unstructured":"Wei L, Huang C, Guo Q, Yang Z, Zhang Z, Alexandropoulos GC, Debbah M, Yuen C. Joint channel estimation and signal recovery for ris-empowered multiuser communications. IEEE Trans Commun. 2022;70(7):4640\u20134655.","journal-title":"IEEE Trans Commun"},{"issue":"1","key":"e_1_3_3_21_2","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1109\/LWC.2022.3217294","article-title":"Deep learning-based channel estimation for double-ris aided massive mimo system","volume":"12","author":"Liu M","year":"2022","unstructured":"Liu M, Li X, Ning B, Huang C, Sun S, Yuen C. Deep learning-based channel estimation for double-ris aided massive mimo system. IEEE Wirel Commun Lett. 2022;12(1):70\u201374.","journal-title":"IEEE Wirel Commun Lett"},{"key":"e_1_3_3_22_2","doi-asserted-by":"crossref","unstructured":"Wan Z Gao Z Alouini MS. Broadband channel estimation for intelligent reflecting surface aided mmwave massive mimo systems. Paper presented at: ICC 2020-2020 IEEE International Conference on Communications (ICC); 2020 Jun 7\u201311; Dublin Ireland.","DOI":"10.1109\/ICC40277.2020.9149146"},{"issue":"10","key":"e_1_3_3_23_2","doi-asserted-by":"crossref","first-page":"6315","DOI":"10.1109\/TWC.2021.3073309","article-title":"Pruning the pilots: Deep learning-based pilot design and channel estimation for mimo-ofdm systems","volume":"20","author":"Mashhadi MB","year":"2021","unstructured":"Mashhadi MB, G\u00fcnd\u00fcz D. Pruning the pilots: Deep learning-based pilot design and channel estimation for mimo-ofdm systems. IEEE Trans Wirel Commun. 2021;20(10):6315\u20136328.","journal-title":"IEEE Trans Wirel Commun"},{"issue":"7","key":"e_1_3_3_24_2","doi-asserted-by":"crossref","first-page":"4732","DOI":"10.1109\/TCOMM.2021.3064949","article-title":"Terahertz massive mimo with holographic reconfigurable intelligent surfaces","volume":"69","author":"Wan Z","year":"2021","unstructured":"Wan Z, Gao Z, Gao F, Di Renzo M, Alouini M-S. Terahertz massive mimo with holographic reconfigurable intelligent surfaces. IEEE Trans Commun. 2021;69(7):4732\u20134750.","journal-title":"IEEE Trans Commun"},{"issue":"6","key":"e_1_3_3_25_2","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1109\/MWC.001.2000534","article-title":"Deep learning based channel extrapolation for large-scale antenna systems: Opportunities, challenges and solutions","volume":"28","author":"Zhang S","year":"2021","unstructured":"Zhang S, Liu Y, Gao F, Xing C, An J, Dobre OA. Deep learning based channel extrapolation for large-scale antenna systems: Opportunities, challenges and solutions. IEEE Wirel Commun. 2021;28(6):160\u2013167.","journal-title":"IEEE Wirel Commun"},{"issue":"11","key":"e_1_3_3_26_2","doi-asserted-by":"crossref","first-page":"7669","DOI":"10.1109\/TWC.2021.3087318","article-title":"Deep learning-based antenna selection and CSI extrapolation in massive MIMO systems","volume":"20","author":"Lin B","year":"2021","unstructured":"Lin B, Gao F, Zhang S, Zhou T, Alkhateeb A. Deep learning-based antenna selection and CSI extrapolation in massive MIMO systems. IEEE Trans Wirel Commun. 2021;20(11):7669\u20137681.","journal-title":"IEEE Trans Wirel Commun"},{"issue":"6","key":"e_1_3_3_27_2","doi-asserted-by":"crossref","first-page":"1921","DOI":"10.1109\/LCOMM.2021.3064596","article-title":"Ordinary differential equation-based CNN for channel extrapolation over RIS-assisted communication","volume":"25","author":"Xu M","year":"2021","unstructured":"Xu M, Zhang S, Zhong C, Ma J, Dobre OA. Ordinary differential equation-based CNN for channel extrapolation over RIS-assisted communication. IEEE Commun Lett. 2021;25(6):1921\u20131925.","journal-title":"IEEE Commun Lett"},{"issue":"12","key":"e_1_3_3_28_2","doi-asserted-by":"crossref","first-page":"2644","DOI":"10.1109\/LWC.2021.3110305","article-title":"Deep learning-based RIS channel extrapolation with element-grouping","volume":"10","author":"Zhang S","year":"2021","unstructured":"Zhang S, Zhang S, Gao F, Ma J, Dobre OA. Deep learning-based RIS channel extrapolation with element-grouping. IEEE Wirel Commun Lett. 2021;10(12):2644\u20132648.","journal-title":"IEEE Wirel Commun Lett"},{"key":"e_1_3_3_29_2","doi-asserted-by":"crossref","first-page":"19530","DOI":"10.1109\/ACCESS.2020.2968456","article-title":"GMD-based hybrid beamforming for large reconfigurable intelligent surface assisted millimeter-Wave massive MIMO","volume":"8","author":"Ying K","year":"2020","unstructured":"Ying K, Gao Z, Lyu S, Wu Y, Wang H, Alouini MS. GMD-based hybrid beamforming for large reconfigurable intelligent surface assisted millimeter-Wave massive MIMO. IEEE Access. 2020;8:19530\u201319539.","journal-title":"IEEE Access"},{"issue":"8","key":"e_1_3_3_30_2","doi-asserted-by":"crossref","first-page":"1809","DOI":"10.1109\/JSAC.2020.3000813","article-title":"Hybrid beamforming for reconfigurable intelligent surface based multi-user communications: Achievable rates with limited discrete phase shifts","volume":"38","author":"Di B","year":"2020","unstructured":"Di B, Zhang H, Song L, Li Y, Han Z, Poor HV. Hybrid beamforming for reconfigurable intelligent surface based multi-user communications: Achievable rates with limited discrete phase shifts. IEEE J Sel Areas Commun. 2020;38(8):1809\u20131822.","journal-title":"IEEE J Sel Areas Commun"},{"key":"e_1_3_3_31_2","doi-asserted-by":"crossref","unstructured":"Ahn Y Shim B. Deep learning-based beamforming for intelligent reflecting surface-assisted mmWave systems. Paper presented at: 2021 International Conference on Information and Communication Technology Convergence (ICTC); 2021 Oct 20\u201322; Jeju Island Korea.","DOI":"10.1109\/ICTC52510.2021.9621150"},{"issue":"7","key":"e_1_3_3_32_2","doi-asserted-by":"crossref","first-page":"1041","DOI":"10.1109\/LWC.2020.2980225","article-title":"Hybrid precoding design for reconfigurable intelligent surface aided mmWave communication systems","volume":"9","author":"Pradhan C","year":"2020","unstructured":"Pradhan C, Li A, Song L, Vucetic B, Li Y. Hybrid precoding design for reconfigurable intelligent surface aided mmWave communication systems. IEEE Wirel Commun Lett. 2020;9(7):1041\u20131045.","journal-title":"IEEE Wirel Commun Lett"},{"issue":"11","key":"e_1_3_3_33_2","doi-asserted-by":"crossref","first-page":"13905","DOI":"10.1109\/TVT.2020.3024756","article-title":"Beyond intelligent reflecting surfaces: Reflective-transmissive metasurface aided communications for full-dimensional coverage extension","volume":"69","author":"Zhang S","year":"2020","unstructured":"Zhang S, Zhang H, Di B, Tan Y, Han Z, Song L. Beyond intelligent reflecting surfaces: Reflective-transmissive metasurface aided communications for full-dimensional coverage extension. IEEE Trans Veh Technol. 2020;69(11):13905\u201313909.","journal-title":"IEEE Trans Veh Technol"},{"key":"e_1_3_3_34_2","doi-asserted-by":"crossref","unstructured":"Youn Y Lee C Kim D Chang S Hwang M Jun D Chae C-B Hong W. Demo: Transparent intelligent surfaces for sub-6 GHz and mmWave B5G\/6G systems. Paper presented at: 2022 IEEE International Conference on Communications Workshops (ICC Workshops); 2022 May 16\u201320; Seoul Korea.","DOI":"10.1109\/ICCWorkshops53468.2022.9915018"},{"issue":"18","key":"e_1_3_3_35_2","doi-asserted-by":"crossref","first-page":"29292","DOI":"10.1364\/OE.435648","article-title":"Transparent dynamic metasurface for a visually unaffected reconfigurable intelligent surface: Controlling transmission\/reflection and making a window into an RF lens","volume":"29","author":"Kitayama D","year":"2021","unstructured":"Kitayama D, Hama Y, Goto K, Miyachi K, Motegi T, Kagaya O. Transparent dynamic metasurface for a visually unaffected reconfigurable intelligent surface: Controlling transmission\/reflection and making a window into an RF lens. Opt Express. 2021;29(18):29292\u201329307.","journal-title":"Opt Express"},{"issue":"10","key":"e_1_3_3_36_2","doi-asserted-by":"crossref","first-page":"7063","DOI":"10.1109\/TCOMM.2021.3098696","article-title":"Hybrid spherical- and planar-wave modeling and DCNN-powered estimation of Terahertz ultra-massive MIMO channels","volume":"69","author":"Chen Y","year":"2021","unstructured":"Chen Y, Yan L, Han C. Hybrid spherical- and planar-wave modeling and DCNN-powered estimation of Terahertz ultra-massive MIMO channels. IEEE Trans Commun. 2021;69(10):7063\u20137076.","journal-title":"IEEE Trans Commun"},{"issue":"14","key":"e_1_3_3_37_2","doi-asserted-by":"crossref","first-page":"14540","DOI":"10.1109\/JSEN.2022.3182881","article-title":"Joint hybrid 3D beamforming relying on sensor-based training for reconfigurable intelligent surface aided TeraHertz-based multiuser massive MIMO systems","volume":"22","author":"Wang X","year":"2022","unstructured":"Wang X, Lin Z, Lin F, Hanzo L. Joint hybrid 3D beamforming relying on sensor-based training for reconfigurable intelligent surface aided TeraHertz-based multiuser massive MIMO systems. IEEE Sensors J. 2022;22(14):14540\u201314552.","journal-title":"IEEE Sensors J"},{"issue":"4","key":"e_1_3_3_38_2","doi-asserted-by":"crossref","first-page":"2487","DOI":"10.1109\/TWC.2020.3042828","article-title":"Robust transmission design for intelligent reflecting surface-aided secure communication systems with imperfect cascaded CSI","volume":"20","author":"Hong S","year":"2021","unstructured":"Hong S, Pan C, Ren H, Wang K, Chai KK, Nallanathan A. Robust transmission design for intelligent reflecting surface-aided secure communication systems with imperfect cascaded CSI. IEEE Trans Wirel Commun. 2021;20(4):2487\u20132501.","journal-title":"IEEE Trans Wirel Commun"},{"issue":"6","key":"e_1_3_3_39_2","doi-asserted-by":"crossref","first-page":"3913","DOI":"10.1109\/TWC.2022.3222218","article-title":"Robust hybrid beamforming design for multi-RIS assisted MIMO system with imperfect CSI","volume":"22","author":"Chen Z","year":"2022","unstructured":"Chen Z, Tang J, Zhang XY, Wu Q, Chen G, Wong K-K. Robust hybrid beamforming design for multi-RIS assisted MIMO system with imperfect CSI. IEEE Trans Wirel Commun. 2022;22(6):3913\u20133926.","journal-title":"IEEE Trans Wirel Commun"},{"issue":"2","key":"e_1_3_3_40_2","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 W","year":"2022","unstructured":"Xu W, Gan L, Huang C. A robust deep learning-based beamforming design for RIS-assisted multiuser MISO communications with practical constraints. IEEE Trans Cogn Commun Netw. 2022;8(2):694\u2013706.","journal-title":"IEEE Trans Cogn Commun Netw"},{"key":"e_1_3_3_41_2","doi-asserted-by":"crossref","unstructured":"Larsson P. Lattice array receiver and sender for spatially orthonormal MIMO communication. Paper presented at: 2005 IEEE 61st Vehicular Technology Conference; 2005 May 30\u2013Jun 1; Stockholm Sweden.","DOI":"10.1109\/VETECS.2005.1543276"},{"key":"e_1_3_3_42_2","doi-asserted-by":"crossref","unstructured":"Bohagen F Orten P Oien GE. Optimal design of uniform planar antenna arrays for strong line-of-sight MIMO channels. Paper presented at: 2006 IEEE 7th Workshop on Signal Processing Advances in Wireless Communications; 2006 Jul 2\u20135; Cannes France.","DOI":"10.1109\/SPAWC.2006.346341"},{"issue":"7","key":"e_1_3_3_43_2","doi-asserted-by":"crossref","first-page":"4830","DOI":"10.1109\/TWC.2018.2832084","article-title":"Two-level spatial multiplexing using hybrid beamforming for millimeter-wave backhaul","volume":"17","author":"Song X","year":"2018","unstructured":"Song X, Rave W, Babu N, Majhi S, Fettweis G. Two-level spatial multiplexing using hybrid beamforming for millimeter-wave backhaul. IEEE Trans Wirel Commun. 2018;17(7):4830\u20134844.","journal-title":"IEEE Trans Wirel Commun"},{"issue":"10","key":"e_1_3_3_44_2","doi-asserted-by":"crossref","first-page":"2840","DOI":"10.1109\/JSAC.2022.3196090","article-title":"Energy-efficient dynamic-subarray with fixed true-time-delay design for Terahertz wideband hybrid beamforming","volume":"40","author":"Yan L","year":"2022","unstructured":"Yan L, Han C, Yuan J. Energy-efficient dynamic-subarray with fixed true-time-delay design for Terahertz wideband hybrid beamforming. IEEE J Sel Areas Commun. 2022;40(10):2840\u20132854.","journal-title":"IEEE J Sel Areas Commun"},{"issue":"5","key":"e_1_3_3_45_2","doi-asserted-by":"crossref","first-page":"2402","DOI":"10.1109\/TWC.2014.2386335","article-title":"Multi-ray channel modeling and wideband characterization for wireless communications in the Terahertz band","volume":"14","author":"Han C","year":"2015","unstructured":"Han C, Bicen AO, Akyildiz IF. Multi-ray channel modeling and wideband characterization for wireless communications in the Terahertz band. IEEE Trans Wirel Commun. 2015;14(5):2402\u20132412.","journal-title":"IEEE Trans Wirel Commun"},{"issue":"3","key":"e_1_3_3_46_2","doi-asserted-by":"crossref","first-page":"1472","DOI":"10.1109\/TWC.2020.3033825","article-title":"Interference and coverage analysis for Terahertz networks with indoor blockage effects and line-of-sight access point association","volume":"20","author":"Wu Y","year":"2021","unstructured":"Wu Y, Kokkoniemi J, Han C, Juntti M. Interference and coverage analysis for Terahertz networks with indoor blockage effects and line-of-sight access point association. IEEE Trans Wirel Commun. 2021;20(3):1472\u20131486.","journal-title":"IEEE Trans Wirel Commun"},{"key":"e_1_3_3_47_2","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2011.081011.100545"},{"issue":"13","key":"e_1_3_3_48_2","doi-asserted-by":"crossref","first-page":"3393","DOI":"10.1109\/TSP.2018.2831628","article-title":"Spatial- and frequency-wideband effects in millimeter-wave massive MIMO systems","volume":"66","author":"Wang B","year":"2018","unstructured":"Wang B, Gao F, Jin S, Lin H, Li GY. Spatial- and frequency-wideband effects in millimeter-wave massive MIMO systems. IEEE Trans Signal Process. 2018;66(13):3393\u20133406.","journal-title":"IEEE Trans Signal Process"},{"issue":"5","key":"e_1_3_3_49_2","doi-asserted-by":"crossref","first-page":"748","DOI":"10.1109\/LWC.2018.2818160","article-title":"Deep learning for massive MIMO CSI feedback","volume":"7","author":"Wen C-K","year":"2018","unstructured":"Wen C-K, Shih W-T, Jin S. Deep learning for massive MIMO CSI feedback. IEEE Wirel Commun Lett. 2018;7(5):748\u2013751.","journal-title":"IEEE Wirel Commun Lett"},{"key":"e_1_3_3_50_2","unstructured":"Vaswani A Shazeer N Parmar N Uszkoreit J Jones L Gomez AN Kaiser LU Polosukhin I. Attention is all you need. In: Guyon I Luxburg UV Bengio S Wallach H Fergus R Vishwanathan S Garnett R editors. Advances in neural information processing systems. Curran Associates Inc.; 2017."},{"key":"e_1_3_3_51_2","first-page":"1","article-title":"Transformer-empowered 6g intelligent networks: From massive MIMO processing to semantic communication","author":"Wang Y","year":"2022","unstructured":"Wang Y, Gao Z, Zheng D, Chen S, Gunduz D, Poor HV. Transformer-empowered 6g intelligent networks: From massive MIMO processing to semantic communication. IEEE Wirel Commun. 2022;1\u20139.","journal-title":"IEEE Wirel Commun"},{"key":"e_1_3_3_52_2","unstructured":"Tolstikhin IO Houlsby N Kolesnikov A Beyer L Zhai X Unterthiner T Yung J Steiner A Keysers D Uszkoreit J et\u00a0al. MLP-mixer: An all-MLP architecture for vision. Advances in neural information processing systems; 2021. p. 24261\u201324272."},{"issue":"9","key":"e_1_3_3_53_2","doi-asserted-by":"crossref","first-page":"4331","DOI":"10.1109\/TSP.2011.2147784","article-title":"An iteratively weighted MMSE approach to distributed sum-utility maximization for a MIMO interfering broadcast channel","volume":"59","author":"Shi Q","year":"2011","unstructured":"Shi Q, Razaviyayn M, Luo Z-Q, He C. An iteratively weighted MMSE approach to distributed sum-utility maximization for a MIMO interfering broadcast channel. IEEE Trans Signal Process. 2011;59(9):4331\u20134340.","journal-title":"IEEE Trans Signal Process"},{"issue":"2","key":"e_1_3_3_54_2","doi-asserted-by":"crossref","first-page":"270","DOI":"10.1162\/neco.1989.1.2.270","article-title":"A learning algorithm for continually running fully recurrent neural networks","volume":"1","author":"Williams RJ","year":"1989","unstructured":"Williams RJ, Zipser D. A learning algorithm for continually running fully recurrent neural networks. Neural Comput. 1989;1(2):270\u2013280.","journal-title":"Neural Comput"},{"issue":"3","key":"e_1_3_3_55_2","doi-asserted-by":"crossref","first-page":"572","DOI":"10.1016\/j.sigpro.2005.05.030","article-title":"Algorithms for simultaneous sparse approximation. Part i: Greedy pursuit","volume":"86","author":"Tropp JA","year":"2006","unstructured":"Tropp JA, Gilbert AC, Strauss MJ. Algorithms for simultaneous sparse approximation. Part i: Greedy pursuit. Signal Process. 2006;86(3):572\u2013588.","journal-title":"Signal Process"},{"key":"e_1_3_3_56_2","doi-asserted-by":"crossref","first-page":"764","DOI":"10.1109\/TSP.2020.2967175","article-title":"Compressive sensing-based adaptive active user detection and channel estimation: Massive access meets massive MIMO","volume":"68","author":"Ke M","year":"2020","unstructured":"Ke M, Gao Z, Wu Y, Gao X, Schober R. Compressive sensing-based adaptive active user detection and channel estimation: Massive access meets massive MIMO. IEEE Trans Signal Process. 2020;68:764\u2013779.","journal-title":"IEEE Trans Signal Process"},{"issue":"8","key":"e_1_3_3_57_2","doi-asserted-by":"crossref","first-page":"2388","DOI":"10.1109\/JSAC.2021.3087269","article-title":"Model-driven deep learning based channel estimation and feedback for millimeter-wave massive hybrid MIMO systems","volume":"39","author":"Ma X","year":"2021","unstructured":"Ma X, Gao Z, Gao F, Di Renzo M. Model-driven deep learning based channel estimation and feedback for millimeter-wave massive hybrid MIMO systems. IEEE J Sel Areas Commun. 2021;39(8):2388\u20132406.","journal-title":"IEEE J Sel Areas Commun"}],"container-title":["Intelligent Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/spj.science.org\/doi\/pdf\/10.34133\/icomputing.0065","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,6]],"date-time":"2024-11-06T11:58:52Z","timestamp":1730894332000},"score":1,"resource":{"primary":{"URL":"https:\/\/spj.science.org\/doi\/10.34133\/icomputing.0065"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1]]},"references-count":56,"alternative-id":["10.34133\/icomputing.0065"],"URL":"https:\/\/doi.org\/10.34133\/icomputing.0065","relation":{},"ISSN":["2771-5892"],"issn-type":[{"value":"2771-5892","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,1]]},"assertion":[{"value":"2023-02-07","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-10-10","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2024-03-13","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"0065"}}