{"id":"https://openalex.org/W3045954644","doi":"https://doi.org/10.1109/iwcmc48107.2020.9148341","title":"Contention Based Massive Access Scheme for B5G: A Compressive Sensing Method","display_name":"Contention Based Massive Access Scheme for B5G: A Compressive Sensing Method","publication_year":2020,"publication_date":"2020-06-01","ids":{"openalex":"https://openalex.org/W3045954644","doi":"https://doi.org/10.1109/iwcmc48107.2020.9148341","mag":"3045954644"},"language":"en","primary_location":{"id":"doi:10.1109/iwcmc48107.2020.9148341","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iwcmc48107.2020.9148341","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Wireless Communications and Mobile Computing (IWCMC)","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/A5082261154","display_name":"Yanna Bai","orcid":"https://orcid.org/0000-0001-7855-7907"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yanna Bai","raw_affiliation_strings":["State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100344294","display_name":"Wei Chen","orcid":"https://orcid.org/0000-0001-5090-9915"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei Chen","raw_affiliation_strings":["Beijing Engineering Research Center of High-speed Railway Broadband Mobile Communications"],"affiliations":[{"raw_affiliation_string":"Beijing Engineering Research Center of High-speed Railway Broadband Mobile Communications","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100620739","display_name":"Bo Ai","orcid":"https://orcid.org/0000-0001-6850-0595"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bo Ai","raw_affiliation_strings":["Beijing Engineering Research Center of High-speed Railway Broadband Mobile Communications"],"affiliations":[{"raw_affiliation_string":"Beijing Engineering Research Center of High-speed Railway Broadband Mobile Communications","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100350955","display_name":"Zhangdui Zhong","orcid":"https://orcid.org/0000-0001-8889-7374"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhangdui Zhong","raw_affiliation_strings":["Beijing Engineering Research Center of High-speed Railway Broadband Mobile Communications"],"affiliations":[{"raw_affiliation_string":"Beijing Engineering Research Center of High-speed Railway Broadband Mobile Communications","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5082261154"],"corresponding_institution_ids":["https://openalex.org/I21193070"],"apc_list":null,"apc_paid":null,"fwci":0.3521,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.54108782,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1854","last_page":"1859"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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":0.9994000196456909,"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/T11458","display_name":"Advanced Wireless Communication Technologies","score":0.9958000183105469,"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/bottleneck","display_name":"Bottleneck","score":0.8386741876602173},{"id":"https://openalex.org/keywords/random-access","display_name":"Random access","score":0.7873430848121643},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.7852063179016113},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.7422446012496948},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7271174192428589},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.6901658177375793},{"id":"https://openalex.org/keywords/network-packet","display_name":"Network packet","score":0.44070667028427124},{"id":"https://openalex.org/keywords/resource","display_name":"Resource (disambiguation)","score":0.43972480297088623},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.4063003361225128},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3224034905433655},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.119503915309906},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.11338421702384949},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10003963112831116}],"concepts":[{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.8386741876602173},{"id":"https://openalex.org/C101722063","wikidata":"https://www.wikidata.org/wiki/Q218825","display_name":"Random access","level":2,"score":0.7873430848121643},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.7852063179016113},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.7422446012496948},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7271174192428589},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.6901658177375793},{"id":"https://openalex.org/C158379750","wikidata":"https://www.wikidata.org/wiki/Q214111","display_name":"Network packet","level":2,"score":0.44070667028427124},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.43972480297088623},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.4063003361225128},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3224034905433655},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.119503915309906},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.11338421702384949},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10003963112831116},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iwcmc48107.2020.9148341","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iwcmc48107.2020.9148341","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Wireless Communications and Mobile Computing (IWCMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1965956912","https://openalex.org/W2015418199","https://openalex.org/W2017698840","https://openalex.org/W2082029531","https://openalex.org/W2109424135","https://openalex.org/W2127271355","https://openalex.org/W2162409952","https://openalex.org/W2406669631","https://openalex.org/W2514426581","https://openalex.org/W2596873572","https://openalex.org/W2706056020","https://openalex.org/W2755405716","https://openalex.org/W2785640387","https://openalex.org/W2897911430","https://openalex.org/W2959143982","https://openalex.org/W2964133168","https://openalex.org/W2979947699","https://openalex.org/W2989010437","https://openalex.org/W3015801342","https://openalex.org/W6713884384","https://openalex.org/W6769695914"],"related_works":["https://openalex.org/W2595172197","https://openalex.org/W2084856301","https://openalex.org/W2127970246","https://openalex.org/W4382618745","https://openalex.org/W2885125400","https://openalex.org/W2011430815","https://openalex.org/W4321606653","https://openalex.org/W2179545120","https://openalex.org/W4301859063","https://openalex.org/W2949163605"],"abstract_inverted_index":{"The":[0,124],"B5G":[1],"is":[2,132],"expected":[3],"to":[4,53,84,117],"support":[5,54],"multiple":[6],"massive":[7,55],"machine-type":[8,23],"communication":[9],"(mMTC)":[10],"services.":[11],"However,":[12],"limited":[13],"resources":[14],"impede":[15],"the":[16,70,86,93,118,128],"access":[17,27,51,74,82],"of":[18,22,95,122,127],"a":[19,42,64,80],"large":[20],"number":[21],"devices,":[24],"and":[25,88],"existing":[26,96],"frameworks":[28],"are":[29],"not":[30],"efficient":[31],"for":[32,47],"transmitting":[33],"small":[34],"data":[35],"packets.":[36],"In":[37],"this":[38],"paper,":[39],"we":[40,78],"propose":[41],"compressive":[43],"sensing":[44],"(CS)":[45],"approach":[46],"contention":[48,72],"based":[49,73],"random":[50],"scheme":[52,75,83],"connections":[56],"(\u2265":[57],"10":[58,108],"<sup":[59,109],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[60,110],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">6</sup>":[61],"devices)":[62],"within":[63],"certain":[65],"time-frequency":[66],"resource.":[67],"Different":[68],"from":[69],"four-step":[71],"in":[76,113,134],"LTE,":[77],"adopt":[79],"one-step":[81],"save":[85],"energy":[87],"spectrum":[89],"resources.":[90],"It":[91],"breaks":[92],"bottleneck":[94],"CS":[97],"multiuser":[98],"detection":[99],"methods":[100],"which":[101],"have":[102],"poor":[103],"scalability":[104],"(e.g.,":[105],"assuming":[106],"\u2264":[107],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">4</sup>":[111],"devices":[112],"relevant":[114],"literatures)":[115],"due":[116],"high":[119],"computational":[120],"complexity":[121],"CS.":[123],"improved":[125],"performance":[126],"newly":[129],"proposed":[130],"method":[131],"observed":[133],"our":[135],"experimental":[136],"results.":[137]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-01-11T23:08:45.486102","created_date":"2025-10-10T00:00:00"}