{"id":"https://openalex.org/W2996706158","doi":"https://doi.org/10.1109/wcsp.2019.8927940","title":"Predictive Resource Allocation with Interference Coordination by Deep Learning","display_name":"Predictive Resource Allocation with Interference Coordination by Deep Learning","publication_year":2019,"publication_date":"2019-10-01","ids":{"openalex":"https://openalex.org/W2996706158","doi":"https://doi.org/10.1109/wcsp.2019.8927940","mag":"2996706158"},"language":"en","primary_location":{"id":"doi:10.1109/wcsp.2019.8927940","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wcsp.2019.8927940","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 11th International Conference on Wireless Communications and Signal Processing (WCSP)","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/A5039165926","display_name":"Zhaoqi Xu","orcid":null},"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":"Zhaoqi Xu","raw_affiliation_strings":["Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038465404","display_name":"Jia Guo","orcid":"https://orcid.org/0000-0002-2134-7367"},"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":"Jia Guo","raw_affiliation_strings":["Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, 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":["Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":null,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9980999827384949,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9980999827384949,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9929999709129333,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.6660616397857666},{"id":"https://openalex.org/keywords/interference","display_name":"Interference (communication)","score":0.6617728471755981},{"id":"https://openalex.org/keywords/resource-allocation","display_name":"Resource allocation","score":0.6225942373275757},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5351660251617432},{"id":"https://openalex.org/keywords/resource-management","display_name":"Resource management (computing)","score":0.46271416544914246},{"id":"https://openalex.org/keywords/resource","display_name":"Resource (disambiguation)","score":0.42645710706710815},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4221961200237274},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.39998307824134827},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.2497539520263672}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6660616397857666},{"id":"https://openalex.org/C32022120","wikidata":"https://www.wikidata.org/wiki/Q797225","display_name":"Interference (communication)","level":3,"score":0.6617728471755981},{"id":"https://openalex.org/C29202148","wikidata":"https://www.wikidata.org/wiki/Q287260","display_name":"Resource allocation","level":2,"score":0.6225942373275757},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5351660251617432},{"id":"https://openalex.org/C2780609101","wikidata":"https://www.wikidata.org/wiki/Q17156588","display_name":"Resource management (computing)","level":2,"score":0.46271416544914246},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.42645710706710815},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4221961200237274},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.39998307824134827},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.2497539520263672},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wcsp.2019.8927940","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wcsp.2019.8927940","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 11th International Conference on Wireless Communications and Signal Processing (WCSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8","score":0.4099999964237213}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1484040084","https://openalex.org/W1522301498","https://openalex.org/W2095705004","https://openalex.org/W2143365024","https://openalex.org/W2476215804","https://openalex.org/W2519075622","https://openalex.org/W2557283755","https://openalex.org/W2591732277","https://openalex.org/W2616867685","https://openalex.org/W2791838888","https://openalex.org/W2793609888","https://openalex.org/W2807731816","https://openalex.org/W2895588882","https://openalex.org/W2919677675","https://openalex.org/W2936009584","https://openalex.org/W6674330103"],"related_works":["https://openalex.org/W2923452570","https://openalex.org/W206598027","https://openalex.org/W2978610750","https://openalex.org/W2022931285","https://openalex.org/W1589966275","https://openalex.org/W2086872282","https://openalex.org/W2137789903","https://openalex.org/W2153007255","https://openalex.org/W2138781885","https://openalex.org/W2124311718"],"abstract_inverted_index":{"Predictive":[0],"resource":[1],"allocation":[2],"with":[3,119,179],"interference":[4,91],"coordination":[5],"can":[6,154],"provide":[7],"high":[8],"throughput":[9],"for":[10,31,61],"densely":[11],"deployed":[12],"cellular":[13],"network":[14],"by":[15,92],"harnessing":[16],"future":[17,37,76],"average":[18],"channel":[19],"gains":[20],"of":[21,34,68,89,131,188],"mobile":[22],"users":[23],"in":[24,78,160],"a":[25,124,139],"minute-long":[26],"time":[27],"window.":[28],"However,":[29],"except":[30],"the":[32,36,40,58,66,69,79,86,108,128,132,147,152,157,168,175,186,189,192],"necessity":[33],"learning":[35],"information,":[38],"finding":[39],"optimal":[41,59,109,177],"policy":[42,60,110],"incurs":[43],"prohibitive":[44],"computational":[45,182],"complexity.":[46],"In":[47],"this":[48,120],"paper,":[49],"we":[50,72,99,122,137],"resort":[51],"to":[52,126,145,174],"deep":[53],"neural":[54],"networks":[55],"(DNNs)to":[56],"learn":[57,127,155],"heterogeneous":[62],"networks.":[63],"To":[64,117],"show":[65,166],"potential":[67],"DNN-based":[70,170],"solution,":[71],"first":[73],"assume":[74],"that":[75,101,151,167],"information":[77],"prediction":[80],"window":[81],"is":[82,191],"known":[83],"perfectly.":[84],"For":[85],"considered":[87],"problem":[88],"coordinating":[90],"muting":[93],"base":[94],"stations":[95],"and":[96],"user":[97,140],"association,":[98],"find":[100],"there":[102],"exists":[103],"dataset":[104],"bias":[105],"issue,":[106,121],"where":[107],"contains":[111],"much":[112,180],"more":[113],"\u201c0\u201d":[114],"than":[115],"\u201c1\u201d.":[116],"deal":[118],"design":[123,138],"DNN":[125,153,190],"intermediate":[129],"result":[130],"original":[133],"optimization":[134],"problem.":[135],"Then,":[136],"association":[141],"algorithm.":[142],"We":[143],"proceed":[144],"extend":[146],"designed":[148],"DNN,":[149],"such":[150],"from":[156],"historical":[158,193],"data":[159],"an":[161],"end-to-end":[162],"manner.":[163],"Simulation":[164],"results":[165],"proposed":[169],"solution":[171,178],"performs":[172],"closely":[173],"numerically-obtained":[176],"lower":[181],"complexity,":[183],"even":[184],"when":[185],"input":[187],"data.":[194]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}