{"id":"https://openalex.org/W7138956541","doi":"https://doi.org/10.1109/globecom59602.2025.11432350","title":"RIS-Assisted NOMA with Partial CSI and Mutual Coupling: A Machine Learning Approach","display_name":"RIS-Assisted NOMA with Partial CSI and Mutual Coupling: A Machine Learning Approach","publication_year":2025,"publication_date":"2025-12-08","ids":{"openalex":"https://openalex.org/W7138956541","doi":"https://doi.org/10.1109/globecom59602.2025.11432350"},"language":null,"primary_location":{"id":"doi:10.1109/globecom59602.2025.11432350","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom59602.2025.11432350","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2025 - 2025 IEEE Global Communications Conference","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Bile Peng","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Bile Peng","raw_affiliation_strings":["Technische Universität Braunschweig,Institute for Communications Technology,Germany"],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Karl-Ludwig Besser","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Karl-Ludwig Besser","raw_affiliation_strings":["Linköping University,Department of Electrical Engineering,Linköping,Sweden"],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Shanpu Shen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shanpu Shen","raw_affiliation_strings":["University of Macau,State Key Laboratory of Internet of Things for Smart City,China"],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Finn Siegismund-Poschmann","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Finn Siegismund-Poschmann","raw_affiliation_strings":["Freie Universität Berlin,Institute for Computer Science,Germany"],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Ramprasad Raghunath","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ramprasad Raghunath","raw_affiliation_strings":["Technische Universität Braunschweig,Institute for Communications Technology,Germany"],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Daniel M. Mittleman","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Daniel M. Mittleman","raw_affiliation_strings":["Brown University,School of Engineering,USA"],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Vahid Jamali","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vahid Jamali","raw_affiliation_strings":["TU Darmstadt,Department of Electrical Engineering and Information Technology,Germany"],"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Eduard A. Jorswieck","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Eduard A. Jorswieck","raw_affiliation_strings":["Technische Universität Braunschweig,Institute for Communications Technology,Germany"],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":8,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.68188395,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4927","last_page":"4933"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11458","display_name":"Advanced Wireless Communication Technologies","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11458","display_name":"Advanced Wireless Communication Technologies","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11192","display_name":"Underwater Vehicles and Communication Systems","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12079","display_name":"IoT Networks and Protocols","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/precoding","display_name":"Precoding","score":0.7940999865531921},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6875},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.667900025844574},{"id":"https://openalex.org/keywords/channel-state-information","display_name":"Channel state information","score":0.5479999780654907},{"id":"https://openalex.org/keywords/base-station","display_name":"Base station","score":0.536300003528595},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5249999761581421},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.48010000586509705},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.4693000018596649}],"concepts":[{"id":"https://openalex.org/C160562895","wikidata":"https://www.wikidata.org/wiki/Q7239557","display_name":"Precoding","level":4,"score":0.7940999865531921},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7516000270843506},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6875},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.667900025844574},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5552999973297119},{"id":"https://openalex.org/C148063708","wikidata":"https://www.wikidata.org/wiki/Q5072511","display_name":"Channel state information","level":3,"score":0.5479999780654907},{"id":"https://openalex.org/C68649174","wikidata":"https://www.wikidata.org/wiki/Q1379116","display_name":"Base station","level":2,"score":0.536300003528595},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5339000225067139},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5249999761581421},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.48010000586509705},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.4693000018596649},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4526999890804291},{"id":"https://openalex.org/C2775918612","wikidata":"https://www.wikidata.org/wiki/Q994794","display_name":"Noma","level":3,"score":0.4424999952316284},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.41119998693466187},{"id":"https://openalex.org/C152139883","wikidata":"https://www.wikidata.org/wiki/Q252973","display_name":"Mutual information","level":2,"score":0.4009000062942505},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.3547999858856201},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.32519999146461487},{"id":"https://openalex.org/C108037233","wikidata":"https://www.wikidata.org/wiki/Q11375","display_name":"Wireless network","level":3,"score":0.29409998655319214},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.28110000491142273},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.27709999680519104},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.26919999718666077},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.26010000705718994}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/globecom59602.2025.11432350","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom59602.2025.11432350","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2025 - 2025 IEEE Global Communications Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W2341725391","https://openalex.org/W2510906680","https://openalex.org/W2963048054","https://openalex.org/W2963552418","https://openalex.org/W3005476696","https://openalex.org/W3011154968","https://openalex.org/W3034737405","https://openalex.org/W3095415448","https://openalex.org/W3120094264","https://openalex.org/W3133631408","https://openalex.org/W3159402647","https://openalex.org/W3194854077","https://openalex.org/W3209192681","https://openalex.org/W3211603507","https://openalex.org/W4206201004","https://openalex.org/W4210439023","https://openalex.org/W4312653776","https://openalex.org/W4312883044","https://openalex.org/W4386596933","https://openalex.org/W4394595807","https://openalex.org/W4407168515"],"related_works":[],"abstract_inverted_index":{"Non-orthogonal":[0],"multiple":[1,7],"access":[2,8],"(NOMA)":[3],"is":[4,120],"a":[5,57,85,96],"promising":[6],"technique.":[9],"Its":[10],"performance":[11],"depends":[12],"strongly":[13],"on":[14],"the":[15,49,73,108,115,131],"wireless":[16],"channel":[17,100],"property,":[18],"which":[19,46,129],"can":[20],"be":[21],"enhanced":[22],"by":[23,65],"reconfigurable":[24],"intelligent":[25],"surfaces":[26],"(RISs).":[27],"In":[28,53],"this":[29,118],"paper,":[30],"we":[31,55],"jointly":[32],"optimize":[33],"base":[34],"station":[35],"(BS)":[36],"precoding":[37,80],"and":[38,81,106],"RIS":[39,93,112],"configuration":[40],"with":[41],"unsupervised":[42],"machine":[43],"learning":[44],"(ML),":[45],"looks":[47],"for":[48,99],"optimal":[50,78],"solution":[51],"autonomously.":[52],"particular,":[54],"propose":[56],"dedicated":[58],"neural":[59],"network":[60],"(NN)":[61],"architecture":[62],"RISnet":[63],"inspired":[64],"domain":[66,125,132],"knowledge":[67,126],"in":[68,104],"communication.":[69],"Compared":[70],"to":[71,88,124,137],"state-of-the-art,":[72],"proposed":[74],"approach":[75],"combines":[76],"analytical":[77],"BS":[79],"ML-enabled":[82],"RIS,":[83],"has":[84,95],"high":[86],"scalability":[87],"control":[89],"more":[90],"than":[91,141],"1000":[92],"elements,":[94],"low":[97],"requirement":[98],"state":[101],"information":[102],"(CSI)":[103],"input,":[105],"addresses":[107],"mutual":[109],"coupling":[110],"between":[111],"elements.":[113],"Beyond":[114],"considered":[116],"problem,":[117],"work":[119],"an":[121],"early":[122],"contribution":[123],"enabled":[127],"ML,":[128],"exploit":[130],"expertise":[133],"of":[134],"communication":[135],"systems":[136],"design":[138],"better":[139],"approaches":[140],"general":[142],"ML":[143],"methods.":[144]},"counts_by_year":[],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2026-02-06T00:00:00"}