{"id":"https://openalex.org/W7138953131","doi":"https://doi.org/10.1109/globecom59602.2025.11431955","title":"Energy-Efficient Learning-Based Beamforming for ISAC-Enabled V2X Networks","display_name":"Energy-Efficient Learning-Based Beamforming for ISAC-Enabled V2X Networks","publication_year":2025,"publication_date":"2025-12-08","ids":{"openalex":"https://openalex.org/W7138953131","doi":"https://doi.org/10.1109/globecom59602.2025.11431955"},"language":null,"primary_location":{"id":"doi:10.1109/globecom59602.2025.11431955","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom59602.2025.11431955","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":"conference-paper","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/A5130172143","display_name":"Chen Shang","orcid":null},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]},{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN","HK"],"is_corresponding":false,"raw_author_name":"Chen Shang","raw_affiliation_strings":["The Hong Kong University of Science and Technology,Thrust of Internet of Things,Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Hong Kong University of Science and Technology,Thrust of Internet of Things,Guangzhou,China","institution_ids":["https://openalex.org/I889458895","https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051524453","display_name":"Jiadong Yu","orcid":"https://orcid.org/0000-0002-8073-8851"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]},{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN","HK"],"is_corresponding":false,"raw_author_name":"Jiadong Yu","raw_affiliation_strings":["The Hong Kong University of Science and Technology,Thrust of Internet of Things,Guangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Hong Kong University of Science and Technology,Thrust of Internet of Things,Guangzhou,China","institution_ids":["https://openalex.org/I889458895","https://openalex.org/I90610280"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5130015346","display_name":"Dinh Thai Hoang","orcid":null},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Dinh Thai Hoang","raw_affiliation_strings":["University of Technology,School of Electrical and Data Engineering,Sydney,Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Technology,School of Electrical and Data Engineering,Sydney,Australia","institution_ids":["https://openalex.org/I114017466"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"925","last_page":"930"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11392","display_name":"Energy Harvesting in Wireless Networks","score":0.19359999895095825,"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/T11392","display_name":"Energy Harvesting in Wireless Networks","score":0.19359999895095825,"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.14020000398159027,"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/T12791","display_name":"Full-Duplex Wireless Communications","score":0.11180000007152557,"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/beamforming","display_name":"Beamforming","score":0.7749000191688538},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.5544999837875366},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.5297999978065491},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.5239999890327454},{"id":"https://openalex.org/keywords/throughput","display_name":"Throughput","score":0.5034999847412109},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.49160000681877136},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.4490000009536743},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.42899999022483826}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7840999960899353},{"id":"https://openalex.org/C54197355","wikidata":"https://www.wikidata.org/wiki/Q5782992","display_name":"Beamforming","level":2,"score":0.7749000191688538},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.5544999837875366},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5297999978065491},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.5239999890327454},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.5034999847412109},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.49160000681877136},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.4490000009536743},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.42899999022483826},{"id":"https://openalex.org/C148063708","wikidata":"https://www.wikidata.org/wiki/Q5072511","display_name":"Channel state information","level":3,"score":0.4113999903202057},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3926999866962433},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.34599998593330383},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.3452000021934509},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.3208000063896179},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3073999881744385},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.29670000076293945},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2953999936580658},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.29350000619888306},{"id":"https://openalex.org/C59519942","wikidata":"https://www.wikidata.org/wiki/Q650665","display_name":"Drone","level":2,"score":0.2777999937534332},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.27459999918937683},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.27410000562667847},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.2703000009059906},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.26089999079704285}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/globecom59602.2025.11431955","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom59602.2025.11431955","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":[{"score":0.7287839651107788,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1518945650","https://openalex.org/W2973229164","https://openalex.org/W3038819247","https://openalex.org/W3072033075","https://openalex.org/W3193816080","https://openalex.org/W4205204500","https://openalex.org/W4387494819","https://openalex.org/W4388145670","https://openalex.org/W4399767318","https://openalex.org/W4400810430","https://openalex.org/W4401596710","https://openalex.org/W4402187143","https://openalex.org/W4408951702","https://openalex.org/W4412610026","https://openalex.org/W7133192924"],"related_works":[],"abstract_inverted_index":{"This":[0,33],"work":[1],"proposes":[2],"an":[3],"energy-efficient,":[4],"learning-based":[5,98],"beamforming":[6,41,75],"scheme":[7],"for":[8,53],"integrated":[9],"sensing":[10,47,84],"and":[11,22,57,76,83,113,137,147],"communication":[12,81,139],"(ISAC)-enabled":[13],"V2X":[14,26,152],"networks.":[15],"Specifically,":[16],"we":[17,100],"first":[18],"model":[19],"the":[20,36,51,92,107,130],"dynamic":[21,88],"uncertain":[23],"nature":[24],"of":[25,96],"environments":[27],"as":[28],"a":[29,66],"Markov":[30],"Decision":[31],"Process.":[32],"formulation":[34],"allows":[35],"roadside":[37],"unit":[38],"to":[39,72,144],"generate":[40],"decisions":[42],"based":[43],"solely":[44],"on":[45],"current":[46],"information,":[48],"thereby":[49],"eliminating":[50],"need":[52],"frequent":[54],"pilot":[55],"transmissions":[56],"extensive":[58],"channel":[59],"state":[60],"information":[61],"acquisition.":[62],"We":[63],"then":[64],"develop":[65],"deep":[67],"reinforcement":[68],"learning":[69],"(DRL)":[70],"algorithm":[71],"jointly":[73],"optimize":[74],"power":[77],"allocation,":[78],"ensuring":[79],"both":[80],"throughput":[82],"accuracy":[85],"in":[86,150],"highly":[87],"scenario.":[89],"To":[90],"address":[91],"high":[93],"energy":[94,120,135],"demands":[95],"conventional":[97],"schemes,":[99],"embed":[101],"spiking":[102],"neural":[103],"networks":[104],"(SNNs)":[105],"into":[106],"DRL":[108],"framework.":[109],"Leveraging":[110],"their":[111],"event-driven":[112],"sparsely":[114],"activated":[115],"architecture,":[116],"SNNs":[117],"significantly":[118],"enhance":[119],"efficiency":[121],"while":[122],"maintaining":[123],"robust":[124],"performance.":[125],"Simulation":[126],"results":[127],"confirm":[128],"that":[129],"proposed":[131],"method":[132],"achieves":[133],"substantial":[134],"savings":[136],"superior":[138],"performance,":[140],"demonstrating":[141],"its":[142],"potential":[143],"support":[145],"green":[146],"sustainable":[148],"connectivity":[149],"future":[151],"systems.":[153]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2026-03-20T00:00:00"}