{"id":"https://openalex.org/W4414648057","doi":"https://doi.org/10.1109/vtc2025-spring65109.2025.11174567","title":"Heterogeneous Graph Neural Network for Beamforming Design in Cell-Free Massive MIMO with Underlaid D2D Maritime Systems","display_name":"Heterogeneous Graph Neural Network for Beamforming Design in Cell-Free Massive MIMO with Underlaid D2D Maritime Systems","publication_year":2025,"publication_date":"2025-06-17","ids":{"openalex":"https://openalex.org/W4414648057","doi":"https://doi.org/10.1109/vtc2025-spring65109.2025.11174567"},"language":"en","primary_location":{"id":"doi:10.1109/vtc2025-spring65109.2025.11174567","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtc2025-spring65109.2025.11174567","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 101st Vehicular Technology Conference (VTC2025-Spring)","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":"https://openalex.org/A5056797987","display_name":"Haiyou Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I59028903","display_name":"Ocean University of China","ror":"https://ror.org/04rdtx186","country_code":"CN","type":"education","lineage":["https://openalex.org/I59028903"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Haiyou Liu","raw_affiliation_strings":["Faculty of Information Science and Engineering Ocean University of China,Qingdao,China"],"affiliations":[{"raw_affiliation_string":"Faculty of Information Science and Engineering Ocean University of China,Qingdao,China","institution_ids":["https://openalex.org/I59028903"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008480230","display_name":"Zexiao Xie","orcid":"https://orcid.org/0000-0003-4569-0562"},"institutions":[{"id":"https://openalex.org/I59028903","display_name":"Ocean University of China","ror":"https://ror.org/04rdtx186","country_code":"CN","type":"education","lineage":["https://openalex.org/I59028903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zuodong Xie","raw_affiliation_strings":["Faculty of Information Science and Engineering Ocean University of China,Qingdao,China"],"affiliations":[{"raw_affiliation_string":"Faculty of Information Science and Engineering Ocean University of China,Qingdao,China","institution_ids":["https://openalex.org/I59028903"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072510723","display_name":"Jiahao Liu","orcid":"https://orcid.org/0000-0002-5663-3961"},"institutions":[{"id":"https://openalex.org/I59028903","display_name":"Ocean University of China","ror":"https://ror.org/04rdtx186","country_code":"CN","type":"education","lineage":["https://openalex.org/I59028903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiahao Liu","raw_affiliation_strings":["Faculty of Information Science and Engineering Ocean University of China,Qingdao,China"],"affiliations":[{"raw_affiliation_string":"Faculty of Information Science and Engineering Ocean University of China,Qingdao,China","institution_ids":["https://openalex.org/I59028903"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100443971","display_name":"Bohan Li","orcid":"https://orcid.org/0000-0001-7766-9579"},"institutions":[{"id":"https://openalex.org/I59028903","display_name":"Ocean University of China","ror":"https://ror.org/04rdtx186","country_code":"CN","type":"education","lineage":["https://openalex.org/I59028903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bohan Li","raw_affiliation_strings":["Faculty of Information Science and Engineering Ocean University of China,Qingdao,China"],"affiliations":[{"raw_affiliation_string":"Faculty of Information Science and Engineering Ocean University of China,Qingdao,China","institution_ids":["https://openalex.org/I59028903"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5056797987"],"corresponding_institution_ids":["https://openalex.org/I59028903"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.36133082,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11946","display_name":"Antenna Design and Optimization","score":0.9258000254631042,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T11946","display_name":"Antenna Design and Optimization","score":0.9258000254631042,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/beamforming","display_name":"Beamforming","score":0.6674000024795532},{"id":"https://openalex.org/keywords/mimo","display_name":"MIMO","score":0.6658999919891357},{"id":"https://openalex.org/keywords/cellular-network","display_name":"Cellular network","score":0.48179998993873596},{"id":"https://openalex.org/keywords/interference","display_name":"Interference (communication)","score":0.47119998931884766},{"id":"https://openalex.org/keywords/power-control","display_name":"Power control","score":0.459199994802475},{"id":"https://openalex.org/keywords/spectral-efficiency","display_name":"Spectral efficiency","score":0.4560000002384186},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4499000012874603},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.44690001010894775}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7961999773979187},{"id":"https://openalex.org/C54197355","wikidata":"https://www.wikidata.org/wiki/Q5782992","display_name":"Beamforming","level":2,"score":0.6674000024795532},{"id":"https://openalex.org/C207987634","wikidata":"https://www.wikidata.org/wiki/Q176862","display_name":"MIMO","level":3,"score":0.6658999919891357},{"id":"https://openalex.org/C153646914","wikidata":"https://www.wikidata.org/wiki/Q535695","display_name":"Cellular network","level":2,"score":0.48179998993873596},{"id":"https://openalex.org/C32022120","wikidata":"https://www.wikidata.org/wiki/Q797225","display_name":"Interference (communication)","level":3,"score":0.47119998931884766},{"id":"https://openalex.org/C56685638","wikidata":"https://www.wikidata.org/wiki/Q2300474","display_name":"Power control","level":3,"score":0.459199994802475},{"id":"https://openalex.org/C137246740","wikidata":"https://www.wikidata.org/wiki/Q583970","display_name":"Spectral efficiency","level":3,"score":0.4560000002384186},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4499000012874603},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.44690001010894775},{"id":"https://openalex.org/C158207573","wikidata":"https://www.wikidata.org/wiki/Q5747224","display_name":"Heterogeneous network","level":4,"score":0.4408000111579895},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.4205999970436096},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.4027999937534332},{"id":"https://openalex.org/C182448111","wikidata":"https://www.wikidata.org/wiki/Q7281197","display_name":"Radio resource management","level":4,"score":0.35280001163482666},{"id":"https://openalex.org/C165650700","wikidata":"https://www.wikidata.org/wiki/Q4636347","display_name":"3G MIMO","level":4,"score":0.34599998593330383},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.3343999981880188},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.3257000148296356},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.3050000071525574},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3037000000476837},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.30140000581741333},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2896000146865845},{"id":"https://openalex.org/C62793504","wikidata":"https://www.wikidata.org/wiki/Q228327","display_name":"Access network","level":2,"score":0.2542000114917755}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vtc2025-spring65109.2025.11174567","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtc2025-spring65109.2025.11174567","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 101st Vehicular Technology Conference (VTC2025-Spring)","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":12,"referenced_works":["https://openalex.org/W2040978064","https://openalex.org/W2286275639","https://openalex.org/W2965857891","https://openalex.org/W2978631110","https://openalex.org/W3040494884","https://openalex.org/W3132295397","https://openalex.org/W3172408309","https://openalex.org/W3187178498","https://openalex.org/W3215769450","https://openalex.org/W4312531397","https://openalex.org/W4389764476","https://openalex.org/W4391936179"],"related_works":[],"abstract_inverted_index":{"Considering":[0],"the":[1,28,37,47,55,65,69,91,96,106,120,138,141,148],"critical":[2],"issue":[3],"of":[4,40,64,84,109,123],"interference":[5,85,102],"management":[6],"in":[7,17],"cell-free":[8],"massive":[9],"MIMO":[10],"with":[11,36,112,151],"underlaid":[12],"device-todevice":[13],"(CF-mMIMO-D2D)":[14],"maritime":[15],"systems,":[16],"this":[18],"paper,":[19],"we":[20,61],"propose":[21],"a":[22,58],"novel":[23],"approach,":[24],"namely":[25],"CFD-HetGNN,":[26],"utilizing":[27],"heterogeneous":[29,59],"graph":[30],"neural":[31,125,129],"network":[32,126,130],"(HetGNN)":[33],"to":[34,67,105,147],"deal":[35],"joint":[38],"optimization":[39],"beamforming":[41],"and":[42,50,77,99,132],"power":[43,114],"allocation":[44,115],"for":[45],"both":[46],"CF-mMIMO":[48],"users":[49],"D2D":[51,78],"pairs.":[52],"By":[53],"modeling":[54],"CF-mMIMO-D2D":[56],"as":[57,117,119],"graph,":[60],"take":[62],"advantage":[63],"HetGNN":[66],"capture":[68],"complex":[70],"interactions":[71],"among":[72],"access":[73],"points,":[74],"mobile":[75],"stations":[76],"pairs,":[79],"enabling":[80],"an":[81],"efficient":[82],"solution":[83],"mitigation.":[86],"Simulation":[87],"results":[88],"demonstrate":[89],"that":[90],"proposed":[92],"CFD-HetGNN":[93,139],"significantly":[94],"improves":[95],"spectral":[97],"efficiency":[98],"achieves":[100],"superior":[101],"control":[103],"compared":[104],"traditional":[107],"approach":[108],"matched":[110],"filtering":[111],"equal":[113],"(MF-EPA)":[116],"well":[118],"learning-assisted":[121],"methods":[122],"convolutional":[124],"(CNN),":[127],"deep":[128],"(DNN)":[131],"long":[133],"short-term":[134],"memory":[135],"(LSTM).":[136],"Additionally,":[137],"possess":[140],"robust":[142],"scalability,":[143],"making":[144],"it":[145],"applicable":[146],"large-scale":[149],"networks":[150],"low":[152],"complexity.":[153]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-10T00:00:00"}