{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,4]],"date-time":"2026-04-04T18:18:03Z","timestamp":1775326683135,"version":"3.50.1"},"reference-count":78,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"12","license":[{"start":{"date-parts":[[2023,12,1]],"date-time":"2023-12-01T00:00:00Z","timestamp":1701388800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"name":"Ph.D. Grant from the Ministry of the Italian Government Ministero dell\u2019Istruzione, dell\u2019Universit\u00e0 e della Ricerca"},{"name":"Centro Nazionale per la Mobilit\u00e0 Sostenibile (MOST), funded by the Italian Ministry of University and Research under the PNRR funding program"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE J. Sel. Areas Commun."],"published-print":{"date-parts":[[2023,12]]},"DOI":"10.1109\/jsac.2023.3322795","type":"journal-article","created":{"date-parts":[[2023,10,9]],"date-time":"2023-10-09T15:05:39Z","timestamp":1696863939000},"page":"3799-3815","source":"Crossref","is-referenced-by-count":28,"title":["Cooperative Deep-Learning Positioning in mmWave 5G-Advanced Networks"],"prefix":"10.1109","volume":"41","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2953-0481","authenticated-orcid":false,"given":"Bernardo Camajori","family":"Tedeschini","sequence":"first","affiliation":[{"name":"Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB), Politecnico di Milano, Milan, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7104-7015","authenticated-orcid":false,"given":"Monica","family":"Nicoli","sequence":"additional","affiliation":[{"name":"Dipartimento di Ingegneria Gestionale (DIG), Politecnico di Milano, Milan, Italy"}]}],"member":"263","reference":[{"issue":"2","key":"ref1","doi-asserted-by":"crossref","first-page":"1124","DOI":"10.1109\/COMST.2017.2785181","article-title":"Survey of cellular mobile radio localization methods: From 1G to 5G","volume":"20","author":"del Peral-Rosado","year":"2018","journal-title":"IEEE Commun. Surveys Tuts."},{"issue":"1","key":"ref2","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1109\/MCOM.001.2000150","article-title":"Position location for futuristic cellular communications: 5G and beyond","volume":"59","author":"Kanhere","year":"2021","journal-title":"IEEE Commun. Mag."},{"key":"ref3","doi-asserted-by":"crossref","first-page":"214945","DOI":"10.1109\/ACCESS.2020.3039271","article-title":"A survey of machine learning for indoor positioning","volume":"8","author":"Nessa","year":"2020","journal-title":"IEEE Access"},{"issue":"6","key":"ref4","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1109\/MSP.2014.2332611","article-title":"Location-aware communications for 5G networks: How location information can improve scalability, latency, and robustness of 5G","volume":"31","author":"Di Taranto","year":"2014","journal-title":"IEEE Signal Process. Mag."},{"key":"ref5","doi-asserted-by":"crossref","DOI":"10.1016\/j.adhoc.2022.102947","article-title":"Survey on positioning information assisted mmWave beamforming training","volume":"135","author":"Nor","year":"2022","journal-title":"Ad Hoc Netw."},{"issue":"8","key":"ref6","doi-asserted-by":"crossref","first-page":"1637","DOI":"10.1109\/JSAC.2020.3000826","article-title":"Prospective multiple antenna technologies for beyond 5G","volume":"38","author":"Zhang","year":"2020","journal-title":"IEEE J. Sel. Areas Commun."},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2018.2804223"},{"issue":"13","key":"ref8","doi-asserted-by":"crossref","first-page":"4757","DOI":"10.3390\/s22134757","article-title":"Positioning in 5G and 6G networks\u2014A survey","volume":"22","author":"Mogyor\u00f3si","year":"2022","journal-title":"Sensors"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/s11036-018-1154-4"},{"issue":"4","key":"ref10","doi-asserted-by":"crossref","first-page":"1525","DOI":"10.1109\/TSP.2006.889978","article-title":"Hidden Markov models for radio localization in mixed LOS\/NLOS conditions","volume":"55","author":"Morelli","year":"2007","journal-title":"IEEE Trans. Signal Process."},{"key":"ref11","first-page":"1","article-title":"UWB localization in a smart factory: Augmentation methods and experimental assessment","volume":"70","author":"Barbieri","year":"2021","journal-title":"IEEE Trans. Instrum. Meas."},{"issue":"6","key":"ref12","doi-asserted-by":"crossref","first-page":"1728","DOI":"10.1109\/JSAC.2022.3156632","article-title":"Integrated sensing and communications: Toward dual-functional wireless networks for 6G and beyond","volume":"40","author":"Liu","year":"2022","journal-title":"IEEE J. Sel. Areas Commun."},{"issue":"7","key":"ref13","doi-asserted-by":"crossref","first-page":"2206","DOI":"10.1109\/JSAC.2022.3155506","article-title":"Time-division ISAC enabled connected automated vehicles cooperation algorithm design and performance evaluation","volume":"40","author":"Zhang","year":"2022","journal-title":"IEEE J. Sel. Areas Commun."},{"key":"ref14","first-page":"1062","article-title":"Distributed 5G NR-based integrated sensing and communication systems: Frame structure and performance analysis","volume-title":"Proc. 30th Eur. Signal Process. Conf. (EUSIPCO)","author":"Shi"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/2348543.2348578"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/VTC2020-Spring48590.2020.9128640"},{"key":"ref17","first-page":"1","article-title":"Indoor wireless sensor network localization using RSSI based weighting algorithm method","volume-title":"Proc. 6th Int. Conf. Eng., Appl. Sci. Technol.","author":"Sangthong"},{"key":"ref18","volume-title":"Moderator\u2019s Summary for Discussion [Ran93E-R18Prep-10] Expanded and Improved Positioning","year":"2021"},{"key":"ref19","article-title":"6G white paper on localization and sensing","author":"Bourdoux","year":"2020","journal-title":"arXiv:2006.01779"},{"key":"ref20","doi-asserted-by":"crossref","first-page":"30845","DOI":"10.1109\/ACCESS.2021.3059488","article-title":"Joint design of communication and sensing for beyond 5G and 6G systems","volume":"9","author":"Wild","year":"2021","journal-title":"IEEE Access"},{"issue":"12","key":"ref21","doi-asserted-by":"crossref","first-page":"11110","DOI":"10.1109\/TWC.2022.3189788","article-title":"A deep learning approach to location- and orientation-aided 3D beam selection for mmWave communications","volume":"21","author":"Rezaie","year":"2022","journal-title":"IEEE Trans. Wireless Commun."},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2021.3064637"},{"issue":"2","key":"ref23","doi-asserted-by":"crossref","first-page":"1280","DOI":"10.1109\/COMST.2022.3149714","article-title":"A survey of collaborative machine learning using 5G vehicular communications","volume":"24","author":"Balkus","year":"2022","journal-title":"IEEE Commun. Surveys Tuts."},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP49357.2023.10094864"},{"issue":"11","key":"ref25","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1109\/MCOM.011.2100339","article-title":"Positioning and sensing for vehicular safety applications in 5G and beyond","volume":"59","author":"Bartoletti","year":"2021","journal-title":"IEEE Commun. Mag."},{"key":"ref26","first-page":"1","article-title":"Addressing data association by message passing over graph neural networks","volume-title":"Proc. 25th Int. Conf. Inf. Fusion (FUSION)","author":"Tedeschini"},{"issue":"1","key":"ref27","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1016\/j.icte.2017.03.005","article-title":"Cooperative localization in 5G networks: A survey","volume":"3","author":"Zhang","year":"2017","journal-title":"ICT Exp."},{"issue":"12","key":"ref28","doi-asserted-by":"crossref","first-page":"3964","DOI":"10.1109\/TITS.2018.2794405","article-title":"Implicit cooperative positioning in vehicular networks","volume":"19","author":"Soatti","year":"2018","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref29","first-page":"1","article-title":"Location-assisted subspace-based beam alignment in LOS\/NLOS mm-wave V2X communications","volume-title":"Proc. IEEE Int. Conf. Commun. (ICC)","author":"Brambilla"},{"issue":"12","key":"ref30","doi-asserted-by":"crossref","first-page":"3573","DOI":"10.3390\/s20123573","article-title":"Sensor-aided V2X beam tracking for connected automated driving: Distributed architecture and processing algorithms","volume":"20","author":"Brambilla","year":"2020","journal-title":"Sensors"},{"issue":"6","key":"ref31","doi-asserted-by":"crossref","first-page":"1655","DOI":"10.1109\/JSAC.2023.3273769","article-title":"On the latent space of mmWave MIMO channels for NLOS identification in 5G-advanced systems","volume":"41","author":"Tedeschini","year":"2023","journal-title":"IEEE J. Sel. Areas Commun."},{"issue":"7","key":"ref32","doi-asserted-by":"crossref","first-page":"1026","DOI":"10.1109\/JSAC.2010.100907","article-title":"NLOS identification and mitigation for localization based on UWB experimental data","volume":"28","author":"Marano","year":"2010","journal-title":"IEEE J. Sel. Areas Commun."},{"issue":"6","key":"ref33","doi-asserted-by":"crossref","first-page":"1719","DOI":"10.1109\/TCOMM.2012.042712.110035","article-title":"A machine learning approach to ranging error mitigation for UWB localization","volume":"60","author":"Wymeersch","year":"2012","journal-title":"IEEE Trans. Commun."},{"issue":"7","key":"ref34","doi-asserted-by":"crossref","first-page":"1357","DOI":"10.1109\/JSAC.2015.2430191","article-title":"Machine learning for wideband localization","volume":"33","author":"Van Nguyen","year":"2015","journal-title":"IEEE J. Sel. Areas Commun."},{"key":"ref35","first-page":"1","article-title":"Machine learning-based channel classification and its application to IEEE 802.11ad communications","volume-title":"Proc. IEEE Global Commun. Conf.","author":"Kurniawan"},{"issue":"10","key":"ref36","doi-asserted-by":"crossref","first-page":"4311","DOI":"10.1109\/JSEN.2018.2818158","article-title":"NLOS mitigation for UWB localization based on sparse pseudo-input Gaussian process","volume":"18","author":"Yang","year":"2018","journal-title":"IEEE Sensors J."},{"key":"ref37","first-page":"775","article-title":"RADAR: An in-building RF-based user location and tracking system","volume-title":"Proc. IEEE INFOCOM. Conf. Comput. Commun., 19th Annu. Joint Conf. IEEE Comput. Commun. Societies","author":"Bahl"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1145\/1067170.1067193"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/WCNC.2015.7127718"},{"key":"ref40","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1016\/j.pmcj.2015.07.002","article-title":"CSI-MIMO: An efficient Wi-Fi fingerprinting using channel state information with MIMO","volume":"23","author":"Chapre","year":"2015","journal-title":"Pervas. Mobile Comput."},{"key":"ref41","first-page":"1","article-title":"PhaseFi: Phase fingerprinting for indoor localization with a deep learning approach","volume-title":"Proc. IEEE Global Commun. Conf. (GLOBECOM)","author":"Wang"},{"issue":"2","key":"ref42","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1109\/MSP.2015.2496324","article-title":"Device-free radio vision for assisted living: Leveraging wireless channel quality information for human sensing","volume":"33","author":"Savazzi","year":"2016","journal-title":"IEEE Signal Process. Mag."},{"key":"ref43","doi-asserted-by":"crossref","first-page":"18066","DOI":"10.1109\/ACCESS.2017.2749516","article-title":"ConFi: Convolutional neural networks based indoor Wi-Fi localization using channel state information","volume":"5","author":"Chen","year":"2017","journal-title":"IEEE Access"},{"key":"ref44","first-page":"1","article-title":"ResLoc: Deep residual sharing learning for indoor localization with CSI tensors","volume-title":"Proc. IEEE 28th Annu. Int. Symp. Pers., Indoor, Mobile Radio Commun. (PIMRC)","author":"Wang"},{"key":"ref45","first-page":"1","article-title":"CiFi: Deep convolutional neural networks for indoor localization with 5 GHz Wi-Fi","volume-title":"Proc. IEEE Int. Conf. Commun. (ICC)","author":"Wang"},{"key":"ref46","doi-asserted-by":"crossref","first-page":"147571","DOI":"10.1109\/ACCESS.2019.2946870","article-title":"Learning spatiotemporal features of CSI for indoor localization with dual-stream 3D convolutional neural networks","volume":"7","author":"Jing","year":"2019","journal-title":"IEEE Access"},{"key":"ref47","first-page":"1","article-title":"5G positioning\u2014A machine learning approach","volume-title":"Proc. 16th Workshop Positioning, Navigat. Commun. (WPNC)","author":"Malmstrom"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1007\/s11063-019-10073-1"},{"key":"ref49","first-page":"1","article-title":"Deep generative model for simultaneous range error mitigation and environment identification","volume-title":"Proc. IEEE Global Commun. Conf. (GLOBECOM)","author":"Li"},{"issue":"6","key":"ref50","doi-asserted-by":"crossref","first-page":"5133","DOI":"10.1109\/JSEN.2021.3101933","article-title":"Estimating TOA reliability with variational autoencoders","volume":"22","author":"Stahlke","year":"2022","journal-title":"IEEE Sensors J."},{"issue":"4","key":"ref51","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/LSENS.2022.3148910","article-title":"A deep learning-based end-to-end algorithm for 5G positioning","volume":"6","author":"Lv","year":"2022","journal-title":"IEEE Sensors Lett."},{"issue":"7","key":"ref52","doi-asserted-by":"crossref","first-page":"2233","DOI":"10.1109\/JSAC.2022.3157397","article-title":"Toward 5G NR high-precision indoor positioning via channel frequency response: A new paradigm and dataset generation method","volume":"40","author":"Gao","year":"2022","journal-title":"IEEE J. Sel. Areas Commun."},{"issue":"7","key":"ref53","doi-asserted-by":"crossref","first-page":"4556","DOI":"10.1109\/TWC.2021.3060482","article-title":"Learning to localize: A 3D CNN approach to user positioning in massive MIMO-OFDM systems","volume":"20","author":"Wu","year":"2021","journal-title":"IEEE Trans. Wireless Commun."},{"issue":"19","key":"ref54","doi-asserted-by":"crossref","first-page":"5495","DOI":"10.3390\/s20195495","article-title":"Implementing deep learning techniques in 5G IoT networks for 3D indoor positioning: DELTA (deep learning-based co-operative architecture)","volume":"20","author":"El Boudani","year":"2020","journal-title":"Sensors"},{"key":"ref55","first-page":"1","article-title":"Cooperative localization with distributed ADMM over 5G-based VANETs","volume-title":"Proc. IEEE Wireless Commun. Netw. Conf. (WCNC)","author":"Kim"},{"key":"ref56","article-title":"Decentralized federated learning for extended sensing in 6G connected vehicles","volume":"33","author":"Barbieri","year":"2022","journal-title":"Veh. Commun."},{"key":"ref57","volume-title":"Study on NR Positioning Support","year":"2019"},{"key":"ref58","first-page":"2575","article-title":"Microscopic traffic simulation using SUMO","volume-title":"Proc. 21st Int. Conf. Intell. Transp. Syst.","author":"Alvarez Lopez"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511807213"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1002\/0471221104"},{"issue":"7","key":"ref61","doi-asserted-by":"crossref","first-page":"6134","DOI":"10.1109\/TVT.2018.2813058","article-title":"Single-site localization based on a new type of fingerprint for massive MIMO-OFDM systems","volume":"67","author":"Sun","year":"2018","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10590-1_53"},{"key":"ref63","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/j.neunet.2014.09.003","article-title":"Deep learning in neural networks: An overview","volume":"61","author":"Schmidhuber","year":"2015","journal-title":"Neural Netw."},{"issue":"4","key":"ref64","volume-title":"Pattern Recognition and Machine Learning","volume":"4","author":"Bishop","year":"2006"},{"issue":"1","key":"ref65","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1162\/neco.1991.3.1.79","article-title":"Adaptive mixtures of local experts","volume":"3","author":"Jacobs","year":"1991","journal-title":"Neural Comput."},{"key":"ref66","volume-title":"Study on Channel Model for Frequencies From 0.5 to 100 GHz (Rel-16)","year":"2020"},{"key":"ref67","first-page":"441","article-title":"A ray tracing method for modeling indoor wave propagation and penetration","volume-title":"Proc. IEEE Antennas Propag. Soc. Int. Symp.","author":"Yang"},{"issue":"6","key":"ref68","doi-asserted-by":"crossref","first-page":"2336","DOI":"10.1109\/25.901902","article-title":"Applicability of ray-tracing technique for the prediction of outdoor channel characteristics","volume":"49","author":"Li","year":"2000","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref69","first-page":"1901","article-title":"Ray tracing simulations for millimeter wave propagation in 5G wireless communications","volume-title":"Proc. IEEE Int. Symp. Antennas Propag. USNC\/URSI Nat. Radio Sci. Meeting","author":"Hsiao"},{"key":"ref70","doi-asserted-by":"crossref","first-page":"1089","DOI":"10.1109\/ACCESS.2015.2453991","article-title":"Ray tracing for radio propagation modeling: Principles and applications","volume":"3","author":"Yun","year":"2015","journal-title":"IEEE Access"},{"key":"ref71","volume-title":"Guidelines for Evaluation of Radio Interface Technologies for IMT-2020","year":"2017"},{"key":"ref72","first-page":"1","article-title":"Automatic differentiation in PyTorch","volume-title":"Proc. NIPS","author":"Paszke"},{"key":"ref73","article-title":"Adam: A method for stochastic optimization","author":"Kingma","year":"2014","journal-title":"arXiv:1412.6980"},{"issue":"12","key":"ref74","doi-asserted-by":"crossref","first-page":"2481","DOI":"10.1109\/TPAMI.2016.2644615","article-title":"SegNet: A deep convolutional encoder\u2013decoder architecture for image segmentation","volume":"39","author":"Badrinarayanan","year":"2017","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref75","article-title":"Gaussian error linear units (GELUs)","author":"Hendrycks","year":"2016","journal-title":"arXiv:1606.08415"},{"issue":"3","key":"ref76","doi-asserted-by":"crossref","first-page":"276","DOI":"10.1109\/TAP.1986.1143830","article-title":"Multiple emitter location and signal parameter estimation","volume":"AP-34","author":"Schmidt","year":"1986","journal-title":"IEEE Trans. Antennas Propag."},{"key":"ref77","first-page":"1","article-title":"Reduced-complexity direction of arrival estimation using real-valued computation with arbitrary array configurations","volume":"2018","author":"Yan","year":"2018","journal-title":"Int. J. Antennas Propag."},{"key":"ref78","volume-title":"Study on Enhancement of 3GPP Support for 5G V2X Services","year":"2018"}],"container-title":["IEEE Journal on Selected Areas in Communications"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/49\/10334485\/10274097.pdf?arnumber=10274097","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,20]],"date-time":"2025-10-20T17:50:06Z","timestamp":1760982606000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10274097\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12]]},"references-count":78,"journal-issue":{"issue":"12"},"URL":"https:\/\/doi.org\/10.1109\/jsac.2023.3322795","relation":{},"ISSN":["1558-0008","0733-8716"],"issn-type":[{"value":"1558-0008","type":"electronic"},{"value":"0733-8716","type":"print"}],"subject":[],"published":{"date-parts":[[2023,12]]}}}