{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T09:52:23Z","timestamp":1753869143302,"version":"3.41.2"},"reference-count":31,"publisher":"Wiley","issue":"11","license":[{"start":{"date-parts":[[2022,7,20]],"date-time":"2022-07-20T00:00:00Z","timestamp":1658275200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Trans Emerging Tel Tech"],"published-print":{"date-parts":[[2022,11]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Massive spatial modulation (SM) multi\u2010input multi\u2010output (MIMO) system is a promising technique in uplink communications for future mobile communication, due to its power and spectral efficiencies. However, these systems, like other MIMO communications, face the challenge of channel estimation. Pilot\u2010based channel estimation methods result in data rate reduction as well as imposing additional complexity at the receiver side, which is intensified in time\u2010varying channels. Therefore, blind channel estimation is an alternative way to avoid pilot transmission. Considering a time\u2010varying channel and taking the advantages of machine learning techniques, blind channel estimation and data detection for SM uplink multi\u2010user massive MIMO communications is presented in this article. In this regard, a blind multi\u2010user detection based on the expectation\u2010maximization (EM) algorithm, called BMU\u2010EM, is presented first; however, this detector suffers from high computational complexity. In order to mitigate the complexity problem, a blind multi\u2010user detection based on sparse Bayesian learning and expectation\u2010maximization, called BMU\u2010SBEM, is proposed. Simulation results show that the BMU\u2010SBEM detector performs almost close to the optimum detector where the perfect channel information is available. Furthermore, the computational complexity of the BMU\u2010SBEM detector increases linearly with the number of users, making it suitable for massive communications in time\u2010varying channels.<\/jats:p>","DOI":"10.1002\/ett.4593","type":"journal-article","created":{"date-parts":[[2022,7,21]],"date-time":"2022-07-21T02:15:50Z","timestamp":1658369750000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Blind detection for spatial modulation uplink multi\u2010user massive MIMO communications: A sparse Bayesian learning\u2010expectation maximization approach"],"prefix":"10.1002","volume":"33","author":[{"given":"Roya","family":"Khanzadeh","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering Shahed University  Tehran Iran"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0715-4710","authenticated-orcid":false,"given":"Mahmoud Ferdosizade","family":"Naeiny","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering Shahed University  Tehran Iran"}]}],"member":"311","published-online":{"date-parts":[[2022,7,20]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/MCOM.2014.6736761"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9781139208437"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2808500"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.aeue.2018.11.020"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/MCOM.2016.7509396"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.1002\/ett.2905"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2019.2929453"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/JSYST.2020.2993704"},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2016.2645201"},{"key":"e_1_2_10_11_1","first-page":"103","article-title":"Receivers for the uplink of multiuser generalized spatial modulation MIMO systems","volume":"35","author":"Calpa Juajinoy JJ","year":"2020","journal-title":"J Commun Inf Syst"},{"key":"e_1_2_10_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2015.2411651"},{"key":"e_1_2_10_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/LCOMM.2016.2577627"},{"key":"e_1_2_10_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/CC.2017.8246340"},{"key":"e_1_2_10_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2019.2930285"},{"key":"e_1_2_10_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCOMM.2020.3018184"},{"key":"e_1_2_10_17_1","doi-asserted-by":"crossref","unstructured":"TuY GuiL QinQ WenH.Sparse detection for spatial modulation in multiple access channels. 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