{"id":"https://openalex.org/W4317418978","doi":"https://doi.org/10.1109/vtc2022-fall57202.2022.10013030","title":"Multi channel spectrum prediction algorithm based on GCN and LSTM","display_name":"Multi channel spectrum prediction algorithm based on GCN and LSTM","publication_year":2022,"publication_date":"2022-09-01","ids":{"openalex":"https://openalex.org/W4317418978","doi":"https://doi.org/10.1109/vtc2022-fall57202.2022.10013030"},"language":"en","primary_location":{"id":"doi:10.1109/vtc2022-fall57202.2022.10013030","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtc2022-fall57202.2022.10013030","pdf_url":null,"source":{"id":"https://openalex.org/S4363607792","display_name":"2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)","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/A5100399276","display_name":"Han Zhang","orcid":"https://orcid.org/0000-0002-0166-1973"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Han Zhang","raw_affiliation_strings":["Harbin Engineering University,College of Information and Communication Engineering,Harbin,China","College of Information and Communication Engineering, Harbin Engineering University, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Engineering University,College of Information and Communication Engineering,Harbin,China","institution_ids":["https://openalex.org/I151727225"]},{"raw_affiliation_string":"College of Information and Communication Engineering, Harbin Engineering University, Harbin, China","institution_ids":["https://openalex.org/I151727225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018710096","display_name":"Qiao Tian","orcid":"https://orcid.org/0000-0001-8177-7724"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiao Tian","raw_affiliation_strings":["Harbin Engineering University,College of Computer Science and Technology,Harbin,China","College of Computer Science and Technology, Harbin Engineering University, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Engineering University,College of Computer Science and Technology,Harbin,China","institution_ids":["https://openalex.org/I151727225"]},{"raw_affiliation_string":"College of Computer Science and Technology, Harbin Engineering University, Harbin, China","institution_ids":["https://openalex.org/I151727225"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088532802","display_name":"Yu Han","orcid":"https://orcid.org/0000-0002-8155-1706"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Han","raw_affiliation_strings":["Harbin Engineering University,College of Information and Communication Engineering,Harbin,China","College of Information and Communication Engineering, Harbin Engineering University, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Engineering University,College of Information and Communication Engineering,Harbin,China","institution_ids":["https://openalex.org/I151727225"]},{"raw_affiliation_string":"College of Information and Communication Engineering, Harbin Engineering University, Harbin, China","institution_ids":["https://openalex.org/I151727225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I151727225"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T10698","display_name":"Transportation Planning and Optimization","score":0.9236999750137329,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9193000197410583,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/burstiness","display_name":"Burstiness","score":0.7358882427215576},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7156643271446228},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6363142728805542},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.6146122217178345},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5248351693153381},{"id":"https://openalex.org/keywords/spectrum","display_name":"Spectrum (functional analysis)","score":0.4950543940067291},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4775743782520294},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4095659852027893},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.350608766078949},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3240832984447479},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.25212231278419495},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15285766124725342},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.09053865075111389},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.07699370384216309}],"concepts":[{"id":"https://openalex.org/C2781023610","wikidata":"https://www.wikidata.org/wiki/Q17006304","display_name":"Burstiness","level":3,"score":0.7358882427215576},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7156643271446228},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6363142728805542},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.6146122217178345},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5248351693153381},{"id":"https://openalex.org/C156778621","wikidata":"https://www.wikidata.org/wiki/Q1365748","display_name":"Spectrum (functional analysis)","level":2,"score":0.4950543940067291},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4775743782520294},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4095659852027893},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.350608766078949},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3240832984447479},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.25212231278419495},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15285766124725342},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09053865075111389},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.07699370384216309},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C158379750","wikidata":"https://www.wikidata.org/wiki/Q214111","display_name":"Network packet","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vtc2022-fall57202.2022.10013030","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtc2022-fall57202.2022.10013030","pdf_url":null,"source":{"id":"https://openalex.org/S4363607792","display_name":"2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.4000000059604645}],"awards":[],"funders":[{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1971130674","https://openalex.org/W2022002249","https://openalex.org/W2605049359","https://openalex.org/W2618238625","https://openalex.org/W2756203131","https://openalex.org/W2885642955","https://openalex.org/W2907492528","https://openalex.org/W2908997014","https://openalex.org/W2969014469","https://openalex.org/W3006182894","https://openalex.org/W3016147814","https://openalex.org/W3080253043","https://openalex.org/W3088383832","https://openalex.org/W3096464124","https://openalex.org/W3103720336","https://openalex.org/W3106121695","https://openalex.org/W3205971195","https://openalex.org/W4200332451","https://openalex.org/W4210395774","https://openalex.org/W6757355660"],"related_works":["https://openalex.org/W1843717240","https://openalex.org/W2340440348","https://openalex.org/W4392388692","https://openalex.org/W2508200300","https://openalex.org/W2083756677","https://openalex.org/W2737070158","https://openalex.org/W2138256111","https://openalex.org/W1574103160","https://openalex.org/W1591572210","https://openalex.org/W4297850514"],"abstract_inverted_index":{"With":[0],"the":[1,21,53,81,95,103,122],"increasingly":[2],"serious":[3],"shortage":[4],"of":[5,28,47,55,83,91,97,105],"spectrum":[6,8,13,29,34,41,56,75,115],"resources,":[7],"dynamic":[9],"access":[10],"based":[11,51,111],"on":[12,52,112],"prediction":[14,35],"technology":[15],"is":[16,36,88],"widely":[17],"recognized.":[18],"Due":[19],"to":[20,93,101],"high":[22],"burstiness":[23],"and":[24,58,68],"complex":[25],"intrinsic":[26],"correlation":[27,54,96],"monitoring":[30,42],"data,":[31],"high-precision":[32],"multi-channel":[33,74,106],"challenging.":[37],"This":[38,77],"paper":[39,78,127],"constructs":[40],"data":[43,50],"as":[44,100],"a":[45,60,113],"kind":[46],"graph":[48,61,84],"structure":[49],"itself,":[57],"designs":[59],"network":[62],"model":[63,123],"combining":[64],"Graph":[65],"convolution":[66],"network(GCN)":[67],"Long-short":[69],"term":[70],"memory":[71],"network(LSTM)":[72],"for":[73],"prediction.":[76,107],"creatively":[79],"introduces":[80],"method":[82],"network.":[85],"And":[86],"GCN":[87],"used":[89],"instead":[90],"CNN":[92],"extract":[94],"channels,":[98],"so":[99],"improve":[102],"accuracy":[104],"Experiments":[108],"are":[109],"conducted":[110],"real-world":[114],"measurement":[116],"dataset.":[117],"The":[118],"results":[119],"show":[120],"that":[121],"proposed":[124],"in":[125],"this":[126],"has":[128],"better":[129],"predictive":[130],"performance":[131],"compared":[132],"with":[133],"other":[134],"methods.":[135]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}