{"id":"https://openalex.org/W2916926743","doi":"https://doi.org/10.1109/glocom.2018.8647254","title":"Deep Spatiotemporal Partially Overlapping Channel Allocation: Joint CNN and Activity Vector Approach","display_name":"Deep Spatiotemporal Partially Overlapping Channel Allocation: Joint CNN and Activity Vector Approach","publication_year":2018,"publication_date":"2018-12-01","ids":{"openalex":"https://openalex.org/W2916926743","doi":"https://doi.org/10.1109/glocom.2018.8647254","mag":"2916926743"},"language":"en","primary_location":{"id":"doi:10.1109/glocom.2018.8647254","is_oa":false,"landing_page_url":"https://doi.org/10.1109/glocom.2018.8647254","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Global Communications Conference (GLOBECOM)","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/A5007662359","display_name":"Fengxiao Tang","orcid":"https://orcid.org/0000-0003-2414-4802"},"institutions":[{"id":"https://openalex.org/I201537933","display_name":"Tohoku University","ror":"https://ror.org/01dq60k83","country_code":"JP","type":"education","lineage":["https://openalex.org/I201537933"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Fengxiao Tang","raw_affiliation_strings":["Graduate School of Information Sciences (GSIS), Tohoku University, Miyagi Ken, Sendai-Shi, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Information Sciences (GSIS), Tohoku University, Miyagi Ken, Sendai-Shi, Japan","institution_ids":["https://openalex.org/I201537933"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015739734","display_name":"Bomin Mao","orcid":"https://orcid.org/0000-0001-7780-5972"},"institutions":[{"id":"https://openalex.org/I201537933","display_name":"Tohoku University","ror":"https://ror.org/01dq60k83","country_code":"JP","type":"education","lineage":["https://openalex.org/I201537933"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Bomin Mao","raw_affiliation_strings":["Graduate School of Information Sciences (GSIS), Tohoku University, Miyagi Ken, Sendai-Shi, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Information Sciences (GSIS), Tohoku University, Miyagi Ken, Sendai-Shi, Japan","institution_ids":["https://openalex.org/I201537933"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063911030","display_name":"Zubair Md. Fadlullah","orcid":"https://orcid.org/0000-0002-4785-2425"},"institutions":[{"id":"https://openalex.org/I201537933","display_name":"Tohoku University","ror":"https://ror.org/01dq60k83","country_code":"JP","type":"education","lineage":["https://openalex.org/I201537933"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Zubair Md. Fadlullah","raw_affiliation_strings":["Graduate School of Information Sciences (GSIS), Tohoku University, Miyagi Ken, Sendai-Shi, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Information Sciences (GSIS), Tohoku University, Miyagi Ken, Sendai-Shi, Japan","institution_ids":["https://openalex.org/I201537933"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013311265","display_name":"Nei Kato","orcid":"https://orcid.org/0000-0001-8769-302X"},"institutions":[{"id":"https://openalex.org/I201537933","display_name":"Tohoku University","ror":"https://ror.org/01dq60k83","country_code":"JP","type":"education","lineage":["https://openalex.org/I201537933"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Nei Kato","raw_affiliation_strings":["Graduate School of Information Sciences (GSIS), Tohoku University, Miyagi Ken, Sendai-Shi, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Information Sciences (GSIS), Tohoku University, Miyagi Ken, Sendai-Shi, Japan","institution_ids":["https://openalex.org/I201537933"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5007662359"],"corresponding_institution_ids":["https://openalex.org/I201537933"],"apc_list":null,"apc_paid":null,"fwci":0.7381,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.7614699,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11158","display_name":"Wireless Networks and Protocols","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10080","display_name":"Energy Efficient Wireless Sensor Networks","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.8165908455848694},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.7326773405075073},{"id":"https://openalex.org/keywords/wireless-network","display_name":"Wireless network","score":0.6255730390548706},{"id":"https://openalex.org/keywords/throughput","display_name":"Throughput","score":0.4821576476097107},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4739137887954712},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.45273134112358093},{"id":"https://openalex.org/keywords/wireless-wan","display_name":"Wireless WAN","score":0.4376089572906494},{"id":"https://openalex.org/keywords/channel-allocation-schemes","display_name":"Channel allocation schemes","score":0.4358285963535309},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.4310779869556427},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.3347657024860382},{"id":"https://openalex.org/keywords/wi-fi-array","display_name":"Wi-Fi array","score":0.31989586353302},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.1651265025138855}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8165908455848694},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.7326773405075073},{"id":"https://openalex.org/C108037233","wikidata":"https://www.wikidata.org/wiki/Q11375","display_name":"Wireless network","level":3,"score":0.6255730390548706},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.4821576476097107},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4739137887954712},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.45273134112358093},{"id":"https://openalex.org/C87379069","wikidata":"https://www.wikidata.org/wiki/Q938054","display_name":"Wireless WAN","level":5,"score":0.4376089572906494},{"id":"https://openalex.org/C114237682","wikidata":"https://www.wikidata.org/wiki/Q5072483","display_name":"Channel allocation schemes","level":3,"score":0.4358285963535309},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.4310779869556427},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3347657024860382},{"id":"https://openalex.org/C152153834","wikidata":"https://www.wikidata.org/wiki/Q1339878","display_name":"Wi-Fi array","level":4,"score":0.31989586353302},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.1651265025138855}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/glocom.2018.8647254","is_oa":false,"landing_page_url":"https://doi.org/10.1109/glocom.2018.8647254","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Global Communications Conference (GLOBECOM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.5}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1522734439","https://openalex.org/W1832693441","https://openalex.org/W2041996794","https://openalex.org/W2052958516","https://openalex.org/W2098854131","https://openalex.org/W2100495367","https://openalex.org/W2104830451","https://openalex.org/W2115579058","https://openalex.org/W2153418687","https://openalex.org/W2154703279","https://openalex.org/W2566425973","https://openalex.org/W2613718673","https://openalex.org/W2617931713","https://openalex.org/W2620303912","https://openalex.org/W2753941074","https://openalex.org/W2767151733","https://openalex.org/W2783684775","https://openalex.org/W2963703618","https://openalex.org/W6620707391","https://openalex.org/W6743446608"],"related_works":["https://openalex.org/W3206458211","https://openalex.org/W2601964555","https://openalex.org/W2607247987","https://openalex.org/W2512844215","https://openalex.org/W2067107826","https://openalex.org/W3007170290","https://openalex.org/W2072849576","https://openalex.org/W2120768828","https://openalex.org/W2033986878","https://openalex.org/W2177164520"],"abstract_inverted_index":{"The":[0,123],"high-speed":[1],"transmission":[2],"has":[3],"become":[4],"extremely":[5],"important":[6],"with":[7,44],"the":[8,18,38,45,70,103,107,112,128],"rapid":[9],"growth":[10],"of":[11,21,40,48,131,136],"network":[12,64,108,129,142],"traffic":[13,46,65,114],"in":[14,33,76,134],"wireless":[15,22,34,49,73,121],"networks.":[16,74],"Because":[17],"available":[19],"bandwidth":[20],"channels":[23],"are":[24,30,66,144],"limited,":[25],"Partially":[26],"Overlapping":[27],"Channels":[28],"(POCs)":[29],"widely":[31],"used":[32],"networks":[35,50],"to":[36,99,120],"maximize":[37],"utilization":[39],"channel":[41,91],"resources.":[42],"However,":[43],"patterns":[47,115],"becoming":[51],"huge":[52],"and":[53,86,116,141],"dynamic,":[54],"conventional":[55,147],"POC":[56,148],"assignment":[57,92,149],"algorithms":[58],"only":[59],"designed":[60],"for":[61,69],"constantly":[62],"generated":[63],"not":[67],"suitable":[68],"new":[71],"generation":[72],"Therefore,":[75],"this":[77],"article,":[78],"a":[79],"joint":[80],"deep":[81],"Covolutional":[82],"Neural":[83],"Network":[84],"(CNN)":[85],"activity":[87],"vector":[88],"based":[89],"intelligent":[90],"algorithm":[93],"is":[94,97],"proposed,":[95],"which":[96],"referred":[98],"as":[100],"CNNAV.":[101],"With":[102],"proposed":[104],"CNNV":[105],"approach,":[106],"can":[109],"learn":[110],"from":[111],"historical":[113],"intelligently":[117],"assign":[118],"POCs":[119],"links.":[122],"simulation":[124],"result":[125],"shows":[126],"that,":[127],"performance":[130],"our":[132],"proposal":[133],"terms":[135],"both":[137],"packets":[138],"loss":[139],"rate":[140],"throughput":[143],"better":[145],"than":[146],"algorithms.":[150]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}