{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,23]],"date-time":"2025-12-23T10:31:33Z","timestamp":1766485893417,"version":"3.37.3"},"reference-count":51,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"3","license":[{"start":{"date-parts":[[2021,4,1]],"date-time":"2021-04-01T00:00:00Z","timestamp":1617235200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,4,1]],"date-time":"2021-04-01T00:00:00Z","timestamp":1617235200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,4,1]],"date-time":"2021-04-01T00:00:00Z","timestamp":1617235200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62001309"],"award-info":[{"award-number":["62001309"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Guangdong Basic and Applied Basic Research Foundation","award":["2019A1515111140"],"award-info":[{"award-number":["2019A1515111140"]}]},{"name":"Shenzhen Science and Technology Program","award":["RCBS20200714114817317"],"award-info":[{"award-number":["RCBS20200714114817317"]}]},{"name":"Open Research Fund from the Shenzhen Research Institute of Big Data","award":["2019ORF01012"],"award-info":[{"award-number":["2019ORF01012"]}]},{"name":"National Key Research, and Development Project","award":["2017YFE0119300"],"award-info":[{"award-number":["2017YFE0119300"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61731018","U1709219"],"award-info":[{"award-number":["61731018","U1709219"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE J. Sel. Top. Signal Process."],"published-print":{"date-parts":[[2021,4]]},"DOI":"10.1109\/jstsp.2021.3058019","type":"journal-article","created":{"date-parts":[[2021,2,10]],"date-time":"2021-02-10T04:36:42Z","timestamp":1612931802000},"page":"832-846","source":"Crossref","is-referenced-by-count":22,"title":["Towards Overfitting Avoidance: Tuning-Free Tensor-Aided Multi-User Channel Estimation for 3D Massive MIMO Communications"],"prefix":"10.1109","volume":"15","author":[{"given":"Lei","family":"Cheng","sequence":"first","affiliation":[]},{"given":"Qingjiang","family":"Shi","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"year":"1993","author":"kay","article-title":"Fundamentals of statistical signal processing, volume I: Estimation theory","key":"ref39"},{"doi-asserted-by":"publisher","key":"ref38","DOI":"10.1109\/TSP.2004.831016"},{"doi-asserted-by":"publisher","key":"ref33","DOI":"10.1088\/0954-898X\/6\/3\/011"},{"year":"2003","author":"beal","journal-title":"Variational algorithms for approximate Bayesian inference","key":"ref32"},{"year":"2016","author":"shi","article-title":"A primer on coordinate descent algorithms","key":"ref31"},{"doi-asserted-by":"publisher","key":"ref30","DOI":"10.1137\/120887795"},{"doi-asserted-by":"publisher","key":"ref37","DOI":"10.1109\/TSP.2007.914345"},{"doi-asserted-by":"publisher","key":"ref36","DOI":"10.1109\/TSP.2020.2975353"},{"doi-asserted-by":"publisher","key":"ref35","DOI":"10.1109\/TSP.2016.2603969"},{"key":"ref34","first-page":"211","article-title":"Sparse Bayesian learning and the relevance vector machine","volume":"1","author":"tipping","year":"2001","journal-title":"J Mach Learn Res"},{"doi-asserted-by":"publisher","key":"ref28","DOI":"10.1109\/SPAWC.2017.8227728"},{"doi-asserted-by":"publisher","key":"ref27","DOI":"10.1109\/TSP.2015.2458788"},{"doi-asserted-by":"publisher","key":"ref29","DOI":"10.1109\/TSP.2017.2690524"},{"doi-asserted-by":"publisher","key":"ref2","DOI":"10.1109\/MCOM.2016.7402270"},{"doi-asserted-by":"publisher","key":"ref1","DOI":"10.1109\/MCOM.2014.6736761"},{"doi-asserted-by":"publisher","key":"ref20","DOI":"10.1109\/78.839978"},{"doi-asserted-by":"publisher","key":"ref22","DOI":"10.1109\/JSAC.2017.2720938"},{"key":"ref21","doi-asserted-by":"crossref","first-page":"984","DOI":"10.1109\/29.32276","article-title":"ESPRIT-estimation of signal parameters via rotational invariance techniques","volume":"37","author":"richard","year":"1989","journal-title":"IEEE Trans Acoust Speech Signal Process"},{"doi-asserted-by":"publisher","key":"ref24","DOI":"10.1109\/GLOCOM.2015.7417413"},{"doi-asserted-by":"publisher","key":"ref23","DOI":"10.1109\/TWC.2017.2710049"},{"doi-asserted-by":"publisher","key":"ref26","DOI":"10.1109\/LCOMM.2015.2493064"},{"doi-asserted-by":"publisher","key":"ref25","DOI":"10.1109\/ACCESS.2019.2908207"},{"doi-asserted-by":"publisher","key":"ref50","DOI":"10.1109\/TSP.2015.2404311"},{"doi-asserted-by":"publisher","key":"ref51","DOI":"10.1137\/1.9780898719062"},{"doi-asserted-by":"publisher","key":"ref10","DOI":"10.1109\/TSP.2010.2068292"},{"key":"ref11","doi-asserted-by":"crossref","first-page":"1356","DOI":"10.1109\/TWC.2014.2365813","article-title":"Channel estimation for massive MIMO using gaussian-mixture bayesian learning","volume":"14","author":"wen","year":"2014","journal-title":"IEEE Trans Wirel Commun"},{"doi-asserted-by":"publisher","key":"ref40","DOI":"10.1137\/07070111X"},{"doi-asserted-by":"publisher","key":"ref12","DOI":"10.1109\/JSTSP.2019.2930893"},{"doi-asserted-by":"publisher","key":"ref13","DOI":"10.1109\/TCOMM.2020.3019077"},{"year":"2012","author":"murphy","journal-title":"Machine Learning A Probabilistic Perspective","key":"ref14"},{"key":"ref15","doi-asserted-by":"crossref","first-page":"5370","DOI":"10.1109\/TWC.2017.2710046","article-title":"Joint angle and delay estimation for 3D massive MIMO systems based on parametric channel modelling","volume":"16","author":"shafin","year":"2017","journal-title":"IEEE Trans Wirel Commun"},{"doi-asserted-by":"publisher","key":"ref16","DOI":"10.1109\/IEEECONF44664.2019.9048890"},{"doi-asserted-by":"publisher","key":"ref17","DOI":"10.1109\/JSTSP.2019.2937392"},{"doi-asserted-by":"publisher","key":"ref18","DOI":"10.1109\/JSTSP.2019.2938880"},{"year":"2004","author":"trees","journal-title":"Detection Estimation and Modulation Theory Optimum Array Processing","key":"ref19"},{"doi-asserted-by":"publisher","key":"ref4","DOI":"10.1109\/TWC.2019.2902557"},{"doi-asserted-by":"publisher","key":"ref3","DOI":"10.1109\/TWC.2019.2950301"},{"doi-asserted-by":"publisher","key":"ref6","DOI":"10.1109\/LWC.2020.2968312"},{"doi-asserted-by":"publisher","key":"ref5","DOI":"10.1109\/TVT.2020.2968095"},{"doi-asserted-by":"publisher","key":"ref8","DOI":"10.1109\/MCOM.2013.6525612"},{"doi-asserted-by":"publisher","key":"ref7","DOI":"10.1109\/MSP.2014.2335236"},{"doi-asserted-by":"publisher","key":"ref49","DOI":"10.1109\/MSP.2018.2844952"},{"doi-asserted-by":"publisher","key":"ref9","DOI":"10.1109\/MWC.2014.6812288"},{"doi-asserted-by":"publisher","key":"ref46","DOI":"10.1109\/JSTSP.2019.2934931"},{"year":"1999","author":"gupta","journal-title":"Matrix Variate Distributions","key":"ref45"},{"doi-asserted-by":"publisher","key":"ref48","DOI":"10.1109\/ACCESS.2016.2551040"},{"doi-asserted-by":"publisher","key":"ref47","DOI":"10.1109\/TSP.2019.2931202"},{"key":"ref42","first-page":"1303","article-title":"Stochastic variational inference","volume":"14","author":"hoffman","year":"2013","journal-title":"J Mach Learn Res"},{"key":"ref41","first-page":"2378","article-title":"Stein variational gradient descent: A general purpose bayesian inference algorithm","author":"liu","year":"2016","journal-title":"Proc Adv Neural Inf Process Syst"},{"doi-asserted-by":"publisher","key":"ref44","DOI":"10.1109\/TPAMI.2018.2889774"},{"key":"ref43","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1561\/2200000001","article-title":"Graphical models, exponential families, and variational inference","volume":"1","author":"wainwright","year":"2008","journal-title":"Found Trends Mach Learn"}],"container-title":["IEEE Journal of Selected Topics in Signal Processing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/4200690\/9393360\/09351615.pdf?arnumber=9351615","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T14:52:44Z","timestamp":1652194364000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9351615\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,4]]},"references-count":51,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.1109\/jstsp.2021.3058019","relation":{},"ISSN":["1932-4553","1941-0484"],"issn-type":[{"type":"print","value":"1932-4553"},{"type":"electronic","value":"1941-0484"}],"subject":[],"published":{"date-parts":[[2021,4]]}}}