{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T19:22:54Z","timestamp":1773775374438,"version":"3.50.1"},"reference-count":195,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["2006683"],"award-info":[{"award-number":["2006683"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Open J. Commun. Soc."],"published-print":{"date-parts":[[2024]]},"DOI":"10.1109\/ojcoms.2024.3446457","type":"journal-article","created":{"date-parts":[[2024,8,20]],"date-time":"2024-08-20T15:51:53Z","timestamp":1724169113000},"page":"5123-5153","source":"Crossref","is-referenced-by-count":25,"title":["Machine Learning for Radio Propagation Modeling: A Comprehensive Survey"],"prefix":"10.1109","volume":"5","author":[{"given":"Manjuladevi","family":"Vasudevan","sequence":"first","affiliation":[{"name":"Electrical and Computer Engineering, University of Central Florida, Orlando, FL, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0387-7038","authenticated-orcid":false,"given":"Murat","family":"Yuksel","sequence":"additional","affiliation":[{"name":"Electrical and Computer Engineering, University of Central Florida, Orlando, FL, USA"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/WCNC.2019.8885668"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/T-VT.1980.23859"},{"key":"ref3","article-title":"COST action 231: Digital mobile radio towards future generation system, final report","volume-title":"Section V-B: On Antenna and Frequency Diversity in GSM. Section V-C: Capacity Study of Frequency Hopping GSM Network","author":"Mogensen","year":"1999"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2015.2453991"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/MCOM.019.2300072"},{"key":"ref6","article-title":"Deep learning for optimal energy-efficient power control in wireless interference networks","author":"Matthiesen","year":"2018","journal-title":"arXiv:1812.06920v1"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/MVT.2019.2921627"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/MSPEC.2019.8727143"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/DySPAN53946.2021.9677342"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/DySPAN.2019.8935734"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/DySPAN.2019.8935725"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICC42927.2021.9500983"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TNSM.2020.3031078"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.3390\/computers12050091"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/SURV.2012.022412.00172"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/SURV.2013.091213.00175"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2999848"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.3390\/electronics10141653"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.sciaf.2023.e01550"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.7251\/IJEEC2206018M"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TAP.2022.3149663"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TAP.2022.3149665"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TAP.2021.3098616"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/s11277-019-06275-4"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCC.2007.905750"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2019.2911558"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/s10846-021-01327-z"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3039271"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/JRPROC.1946.234568"},{"key":"ref30","volume-title":"Wireless Communication Systems in MATLAB","author":"Viswanathan","year":"2020"},{"key":"ref31","volume-title":"Wireless Communications: Principles and Practice","author":"Rappaport","year":"2002"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2000.5340727"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/EDM.2016.7538693"},{"issue":"9","key":"ref34","first-page":"39","article-title":"Computer analysis of the COST 231 Hata model and least squares approximation for path loss estimation at 900MHz on the mountain terrains of the Jos-Plateau, Nigeria","volume":"4","author":"Deme","year":"2013","journal-title":"Comput. Eng. Intell. Syst."},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TAEECE.2013.6557329"},{"key":"ref36","volume-title":"COST Action 231\u2014Digital Mobile Radio Towards Future Generation Systems: Final Report","year":"1999"},{"key":"ref37","first-page":"179","volume-title":"Adaptive Propagation Prediction using Lee\u2019s Model in a Non-Homogeneous Environment","volume":"309","author":"Lopez","year":"1995"},{"key":"ref38","volume-title":"Microcell prediction model","author":"Lee","year":"2024"},{"key":"ref39","article-title":"Coverage and antennas","volume-title":"Wireless & Cellular Telecommunication","author":"Lee","year":"2005"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1002\/9780470930427.ch2"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1002\/9780470930427.ch2"},{"issue":"4","key":"ref42","first-page":"1","article-title":"Validation of Egli model and estimation of Pathloss exponent of a radio signal at VHF band in hilly terrain","volume":"5","author":"Akanni","year":"2020","journal-title":"Int. J. Res. Innov. Appl. Sci."},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/JRPROC.1957.278224"},{"key":"ref44","volume-title":"Egli model\u2014Wikipedia","year":"2024"},{"key":"ref45","volume-title":"Propagation by diffraction","year":"2019"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2007.901902"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/VETECS.2006.1683398"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/SoutheastCon45413.2021.9401929"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3166895"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/ICSENS.2009.5398451"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/MCOM.2012.6211483"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/MCOM.2012.6353680"},{"key":"ref53","volume-title":"OpenCellID","year":"2024"},{"key":"ref54","volume-title":"OpenBmap","year":"2023"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/WOCC53213.2021.9602871"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3201643"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/WiMob50308.2020.9253369"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2964103"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.3390\/s23010475"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3218622"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/GLOBECOM38437.2019.9014187"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.23919\/EuCAP53622.2022.9768903"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/MOCAST52088.2021.9493374"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3185124"},{"key":"ref65","article-title":"A survey of application of machine learning in wireless indoor positioning systems","author":"Sonny","year":"2024","journal-title":"arXiv:2403.04333"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1007\/s11277-017-5119-x"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.3233\/IDA-226750"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3193486"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2985929"},{"key":"ref70","first-page":"1","article-title":"Radio propagation prediction model using convolutional neural networks by deep learning","volume-title":"Proc. 13th Eur. Conf. Antennas Propagat. (EuCAP)","author":"Imai"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1155\/2018\/8489326"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.3390\/app9091908"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1109\/ICOIN53446.2022.9687274"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1109\/PIMRC50174.2021.9569521"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3097633"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1109\/MOCAST.2019.8741751"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.1109\/APWC.2013.6624896"},{"key":"ref78","doi-asserted-by":"publisher","DOI":"10.1016\/j.aeue.2015.06.014"},{"key":"ref79","doi-asserted-by":"publisher","DOI":"10.1109\/LAWP.2005.860213"},{"key":"ref80","doi-asserted-by":"publisher","DOI":"10.1109\/PIMRC.2002.1046748"},{"key":"ref81","doi-asserted-by":"publisher","DOI":"10.1109\/TAP.2016.2617379"},{"key":"ref82","doi-asserted-by":"publisher","DOI":"10.2529\/PIERS070220023434"},{"key":"ref83","first-page":"1","article-title":"A proposal for path loss prediction in urban environments using support vector regression","volume-title":"Proc. Adv. Int. Conf. Telecommun","author":"Timoteo"},{"key":"ref84","doi-asserted-by":"publisher","DOI":"10.3390\/s20071927"},{"key":"ref85","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2010.2050502"},{"key":"ref86","doi-asserted-by":"publisher","DOI":"10.1007\/s11276-021-02682-3"},{"key":"ref87","doi-asserted-by":"publisher","DOI":"10.1155\/2012\/351487"},{"key":"ref88","doi-asserted-by":"publisher","DOI":"10.3390\/telecom1020009"},{"key":"ref89","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2979220"},{"key":"ref90","doi-asserted-by":"publisher","DOI":"10.1145\/3391812.3396274"},{"key":"ref91","doi-asserted-by":"publisher","DOI":"10.1088\/1757-899X\/768\/4\/042038"},{"key":"ref92","doi-asserted-by":"publisher","DOI":"10.1109\/LWC.2020.2994945"},{"key":"ref93","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2014.2372341"},{"key":"ref94","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2020.3033825"},{"key":"ref95","doi-asserted-by":"publisher","DOI":"10.23919\/JCIN.2020.9130434"},{"key":"ref96","doi-asserted-by":"publisher","DOI":"10.1109\/TAP.2022.3161496"},{"key":"ref97","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2021.3060003"},{"key":"ref98","doi-asserted-by":"publisher","DOI":"10.1109\/TAP.2022.3175214"},{"key":"ref99","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313726"},{"key":"ref100","doi-asserted-by":"publisher","DOI":"10.1109\/TAP.2004.835252"},{"key":"ref101","doi-asserted-by":"publisher","DOI":"10.1109\/TNSM.2020.3035442"},{"key":"ref102","doi-asserted-by":"publisher","DOI":"10.1109\/icc42927.2021.9500970"},{"key":"ref103","article-title":"An empirical study on using CNNs for fast radio signal prediction","author":"Ozyegen","year":"2021","journal-title":"arXiv:2006.09245"},{"key":"ref104","doi-asserted-by":"publisher","DOI":"10.1109\/ICCT52962.2021.9658079"},{"key":"ref105","doi-asserted-by":"publisher","DOI":"10.1109\/GLOBECOM42002.2020.9322089"},{"key":"ref106","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3194652"},{"key":"ref107","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2021.3054977"},{"key":"ref108","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3176619"},{"key":"ref109","doi-asserted-by":"publisher","DOI":"10.1109\/JRFID.2023.3285452"},{"key":"ref110","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3217912"},{"key":"ref111","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2947701"},{"key":"ref112","doi-asserted-by":"publisher","DOI":"10.1109\/USNC-URSI52151.2023.10237978"},{"key":"ref113","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2022.3183930"},{"key":"ref114","doi-asserted-by":"publisher","DOI":"10.1109\/ICC40277.2020.9149375"},{"key":"ref115","doi-asserted-by":"publisher","DOI":"10.1007\/s11276-018-1774-4"},{"key":"ref116","volume-title":"Digital Mobile Radio Towards Future Generation Systems","year":"1999"},{"key":"ref117","doi-asserted-by":"publisher","DOI":"10.1109\/VETECS.2005.1543252"},{"key":"ref118","volume-title":"Ensemble methods: Bagging, boosting and stacking","author":"Rocca","year":"2019"},{"key":"ref119","doi-asserted-by":"publisher","DOI":"10.1145\/1963405.1963461"},{"key":"ref120","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939785"},{"key":"ref121","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2018.2880736"},{"key":"ref122","doi-asserted-by":"publisher","DOI":"10.1109\/VTC2021-Fall52928.2021.9625539"},{"key":"ref123","volume-title":"Neural Network Design","author":"Hagan","year":"1996"},{"key":"ref124","doi-asserted-by":"publisher","DOI":"10.1017\/S0305004100030401"},{"key":"ref125","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref126","article-title":"Very deep convolutional networks for large-scale image recognition","author":"Simonyan","year":"2015","journal-title":"arXiv:1409.1556"},{"key":"ref127","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2017.2657381"},{"issue":"1","key":"ref128","first-page":"1929","article-title":"Dropout: A simple way to prevent neural networks from overfitting","volume":"15","author":"Srivastava","year":"2014","journal-title":"J. Mach. Learn. Res."},{"key":"ref129","article-title":"Improving neural networks by preventing co-adaptation of feature detectors","author":"Hinton","year":"2012","journal-title":"arXiv:1207.0580"},{"key":"ref130","article-title":"Bootstrap your own latent: A new approach to self-supervised learning","author":"Grill","year":"2020","journal-title":"arXiv:2006.07733"},{"key":"ref131","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2964103"},{"key":"ref132","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2016.2543139"},{"key":"ref133","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46487-9_43"},{"key":"ref134","volume-title":"Wireless Communications: Principles and Practice","author":"Rappaport","year":"2002"},{"key":"ref135","volume-title":"Wireless Insite em Propagation Software","year":"2024"},{"key":"ref136","volume-title":"Suplacemaker","year":"2024"},{"key":"ref137","volume-title":"Sketchup","year":"2024"},{"key":"ref138","first-page":"1","article-title":"Dominant path prediction model for urban scenarios","volume-title":"Proc. 14th IST Mobile Wireless Commun.","author":"Wahl"},{"key":"ref139","doi-asserted-by":"publisher","DOI":"10.1109\/VETECF.2002.1040665"},{"key":"ref140","volume-title":"Radiomapseer","year":"2024"},{"key":"ref141","volume-title":"Planet dump","year":"2017"},{"key":"ref142","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref143","first-page":"3149","article-title":"LightGBM: A highly efficient gradient boosting decision tree","volume-title":"Proc. 31st Int. Conf. Neural Inf. Process. Syst.","author":"Ke"},{"key":"ref144","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2931072"},{"key":"ref145","doi-asserted-by":"publisher","DOI":"10.1049\/ell2.12631"},{"key":"ref146","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref147","doi-asserted-by":"publisher","DOI":"10.1109\/ICCCN52240.2021.9522192"},{"key":"ref148","author":"Mahammad","year":"2017","journal-title":"Geotiff\u2014A standard image file format for GIS applications"},{"key":"ref149","doi-asserted-by":"publisher","DOI":"10.1016\/j.aeue.2018.07.007"},{"key":"ref150","doi-asserted-by":"publisher","DOI":"10.1002\/9781118502280"},{"key":"ref151","doi-asserted-by":"publisher","DOI":"10.1016\/b978-0-12-181050-4.50010-x"},{"key":"ref152","volume-title":"Discussion paper concerning recommendation ITU-R P.1812\u2014the Bullington diffraction model and its correction","year":"2008"},{"key":"ref153","doi-asserted-by":"publisher","DOI":"10.1049\/el:19920459"},{"key":"ref154","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM.2017.8057113"},{"key":"ref155","doi-asserted-by":"publisher","DOI":"10.1109\/LWC.2014.2321741"},{"key":"ref156","doi-asserted-by":"publisher","DOI":"10.1007\/BF00117832"},{"key":"ref157","doi-asserted-by":"publisher","DOI":"10.1145\/2787394.2787395"},{"key":"ref158","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3111083"},{"key":"ref159","doi-asserted-by":"publisher","DOI":"10.1109\/IPIN.2014.7275466"},{"key":"ref160","doi-asserted-by":"publisher","DOI":"10.1109\/JRFID.2022.3182819"},{"key":"ref161","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2018.2851675"},{"key":"ref162","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3305396"},{"key":"ref163","doi-asserted-by":"publisher","DOI":"10.24425\/opelre.2022.140858"},{"key":"ref164","doi-asserted-by":"publisher","DOI":"10.1109\/ICSensT.2015.7438442"},{"key":"ref165","doi-asserted-by":"publisher","DOI":"10.1109\/PIMRC50174.2021.9569615"},{"key":"ref166","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2899736"},{"key":"ref167","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2020.3003404"},{"key":"ref168","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2023.3234123"},{"key":"ref169","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2014.2308995"},{"key":"ref170","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3069793"},{"key":"ref171","doi-asserted-by":"publisher","DOI":"10.1109\/CCECE53047.2021.9569205"},{"key":"ref172","doi-asserted-by":"publisher","DOI":"10.1109\/SAHCN.2018.8397121"},{"key":"ref173","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2903487"},{"key":"ref174","doi-asserted-by":"publisher","DOI":"10.32604\/cmc.2023.032710"},{"key":"ref175","doi-asserted-by":"publisher","DOI":"10.1109\/TENCON.2011.6129175"},{"key":"ref176","first-page":"17930","article-title":"Automatic WLAN fingerprint radio map generation for accurate indoor positioning based on signal path loss model","volume":"10","author":"Alshami","year":"2015","journal-title":"ARPN J. Eng. Appl. Sci."},{"key":"ref177","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2021.3135700"},{"key":"ref178","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/B978-0-12-813189-3.00004-6","article-title":"Radio maps for fingerprinting in indoor positioning","volume-title":"Geographical and Fingerprinting Data to Create Systems for Indoor Positioning and Indoor\/Outdoor Navigation","author":"Meneses","year":"2019"},{"key":"ref179","doi-asserted-by":"publisher","DOI":"10.1155\/2015\/295652"},{"key":"ref180","doi-asserted-by":"publisher","DOI":"10.1109\/ICOIN.2018.8343215"},{"key":"ref181","first-page":"147","article-title":"Modified random forest algorithm for Wi\u2013Fi indoor localization system","volume-title":"Proc. 8th ICCCI","author":"Luckner"},{"issue":"10","key":"ref182","doi-asserted-by":"crossref","first-page":"3418","DOI":"10.3390\/s21103418","article-title":"An efficient indoor positioning method based on wi-Fi RSS fingerprint and classification algorithm","volume":"21","author":"Ezhumalai","year":"2021","journal-title":"Sensors"},{"key":"ref183","doi-asserted-by":"crossref","first-page":"717","DOI":"10.1049\/iet-com.2015.0469","article-title":"Multi-layer neural network for received signal strength-based indoor localisation","volume":"10","author":"Xu","year":"2016","journal-title":"IET Commun."},{"key":"ref184","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2003.814469"},{"key":"ref185","doi-asserted-by":"publisher","DOI":"10.1007\/s13369-012-0218-1"},{"key":"ref186","first-page":"1012","article-title":"Modeling of indoor positioning systems based on location fingerprinting","volume-title":"Proc. IEEE INFOCOM","author":"Kamol"},{"key":"ref187","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2020.2996564"},{"key":"ref188","doi-asserted-by":"publisher","DOI":"10.3390\/s19030712"},{"key":"ref189","doi-asserted-by":"publisher","DOI":"10.1109\/MWC.2019.1800146"},{"key":"ref190","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2830415"},{"key":"ref191","doi-asserted-by":"publisher","DOI":"10.1109\/MVT.2020.3023682"},{"key":"ref192","doi-asserted-by":"publisher","DOI":"10.3390\/s16122074"},{"key":"ref193","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2014.2343636"},{"key":"ref194","first-page":"548","article-title":"Hybrid-empirical neural model for indoor\/outdoor path loss calculation","volume-title":"Proc. 10th Int. Conf. Telecommun. Modern Satell. Cable Broadcast. Services (TELSIKS)","author":"Miliji\u0107"},{"key":"ref195","first-page":"1","article-title":"Comparison of ANN based models for path loss prediction in indoor environment","volume-title":"Proc. IEEE Veh. Technol. Conf.","author":"Popescu"}],"container-title":["IEEE Open Journal of the Communications Society"],"original-title":[],"link":[{"URL":"https:\/\/ieeexplore.ieee.org\/ielam\/8782661\/10362961\/10640063-aam.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/8782661\/10362961\/10640063.pdf?arnumber=10640063","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,31]],"date-time":"2024-08-31T04:43:50Z","timestamp":1725079430000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10640063\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"references-count":195,"URL":"https:\/\/doi.org\/10.1109\/ojcoms.2024.3446457","relation":{},"ISSN":["2644-125X"],"issn-type":[{"value":"2644-125X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]}}}