{"id":"https://openalex.org/W4390724345","doi":"https://doi.org/10.23919/jcin.2023.10387243","title":"Resource Allocation for URLLC with Parameter Generation Network","display_name":"Resource Allocation for URLLC with Parameter Generation Network","publication_year":2023,"publication_date":"2023-12-01","ids":{"openalex":"https://openalex.org/W4390724345","doi":"https://doi.org/10.23919/jcin.2023.10387243"},"language":"en","primary_location":{"id":"doi:10.23919/jcin.2023.10387243","is_oa":false,"landing_page_url":"http://dx.doi.org/10.23919/jcin.2023.10387243","pdf_url":null,"source":{"id":"https://openalex.org/S4210178728","display_name":"Journal of Communications and Information Networks","issn_l":"2096-1081","issn":["2096-1081","2509-3312"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Communications and Information Networks","raw_type":"journal-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/A5100621604","display_name":"Jiajun Wu","orcid":"https://orcid.org/0000-0002-2813-3249"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiajun Wu","raw_affiliation_strings":["School of Electronics and Information Engineering, Beihang University, Beijing 100191, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Information Engineering, Beihang University, Beijing 100191, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053151490","display_name":"Chengjian Sun","orcid":"https://orcid.org/0000-0002-1733-5005"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengjian Sun","raw_affiliation_strings":["School of Electronics and Information Engineering, Beihang University, Beijing 100191, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Information Engineering, Beihang University, Beijing 100191, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082950698","display_name":"Chenyang Yang","orcid":"https://orcid.org/0000-0003-0058-0765"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenyang Yang","raw_affiliation_strings":["School of Electronics and Information Engineering, Beihang University, Beijing 100191, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Information Engineering, Beihang University, Beijing 100191, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100621604"],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":0.3487,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.68252875,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"8","issue":"4","first_page":"319","last_page":"328"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9865999817848206,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9825999736785889,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6906485557556152},{"id":"https://openalex.org/keywords/resource-allocation","display_name":"Resource allocation","score":0.5691046714782715},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5432599186897278},{"id":"https://openalex.org/keywords/wireless-network","display_name":"Wireless network","score":0.4996507167816162},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43581101298332214},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.4007369875907898},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.3820682764053345},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.36728113889694214},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32006290555000305},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.19262608885765076},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1293918490409851},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.11203780770301819}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6906485557556152},{"id":"https://openalex.org/C29202148","wikidata":"https://www.wikidata.org/wiki/Q287260","display_name":"Resource allocation","level":2,"score":0.5691046714782715},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5432599186897278},{"id":"https://openalex.org/C108037233","wikidata":"https://www.wikidata.org/wiki/Q11375","display_name":"Wireless network","level":3,"score":0.4996507167816162},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43581101298332214},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.4007369875907898},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3820682764053345},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.36728113889694214},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32006290555000305},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.19262608885765076},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1293918490409851},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.11203780770301819}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/jcin.2023.10387243","is_oa":false,"landing_page_url":"http://dx.doi.org/10.23919/jcin.2023.10387243","pdf_url":null,"source":{"id":"https://openalex.org/S4210178728","display_name":"Journal of Communications and Information Networks","issn_l":"2096-1081","issn":["2096-1081","2509-3312"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Communications and Information Networks","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2391251536","https://openalex.org/W2465918047","https://openalex.org/W2362198218","https://openalex.org/W2019521278","https://openalex.org/W1984922432","https://openalex.org/W2375008505","https://openalex.org/W2086348228","https://openalex.org/W2136712919","https://openalex.org/W3133147449","https://openalex.org/W1901143057"],"abstract_inverted_index":{"Deep":[0],"learning":[1],"enables":[2],"real-time":[3],"resource":[4,90],"allocation":[5,64,91,176],"for":[6],"ultra-reliable":[7],"and":[8,28,62,113,155,174,200,203,213],"low-latency":[9],"communications":[10],"(URLLC),":[11],"one":[12],"of":[13,32,39,71,74,101,116,198],"the":[14,19,24,36,40,110,117,121,126,129,138,147,152,171,179,189,196,218],"major":[15],"use":[16,38],"cases":[17],"in":[18,43,66,137,163],"next-generation":[20],"cellular":[21],"networks.":[22],"Yet":[23],"high":[25],"training":[26,165,211,215],"complexity":[27],"weak":[29],"generalization":[30],"ability":[31],"neural":[33,76],"networks":[34,77],"impede":[35],"practical":[37],"learning-based":[41,220],"methods":[42],"dynamic":[44],"wireless":[45,201],"environments.":[46],"To":[47],"overcome":[48],"these":[49],"obstacles,":[50],"we":[51],"propose":[52],"a":[53,81,89,94,143,185],"parameter":[54],"generation":[55],"network":[56,131],"(PGN)":[57],"to":[58,87,108,184,195],"efficiently":[59],"learn":[60,88,109,151],"bandwidth":[61,173],"power":[63,175],"policies":[65,177],"URLLC.":[67],"The":[68,98],"PGN":[69],"consists":[70],"two":[72],"types":[73],"fully-connected":[75],"(FNNs).":[78],"One":[79],"is":[80,85,132],"policy":[82,92,118,130],"network,":[83],"which":[84,105],"used":[86],"or":[93],"Lagrangian":[95],"multiplier":[96],"function.":[97],"other":[99],"type":[100],"FNNs":[102],"are":[103,106,204],"hypernetworks,":[104,128],"designed":[107],"weight":[111,153],"matrices":[112,154],"bias":[114,156],"vectors":[115,157],"network.":[119],"Only":[120],"hypernetworks":[122,148],"require":[123],"training.":[124],"Using":[125],"well-trained":[127],"generated":[133],"through":[134],"forward":[135],"propagation":[136],"test":[139],"phase.":[140],"By":[141],"introducing":[142],"simple":[144],"data":[145],"processing,":[146],"can":[149,191],"well":[150,193],"by":[158,178],"inputting":[159],"their":[160],"indices,":[161],"resulting":[162],"low":[164],"cost.":[166],"Simulation":[167],"results":[168],"demonstrate":[169],"that":[170],"learned":[172],"PGNs":[180,190],"perform":[181],"very":[182],"close":[183],"numerical":[186],"algorithm.":[187],"Moreover,":[188],"be":[192],"generalized":[194],"number":[197],"users":[199],"channels,":[202],"with":[205],"significantly":[206],"lower":[207],"memory":[208],"costs,":[209],"fewer":[210],"samples,":[212],"shorter":[214],"time":[216],"than":[217],"traditional":[219],"methods.":[221]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-27T14:29:43.386196","created_date":"2025-10-10T00:00:00"}