{"id":"https://openalex.org/W4414539063","doi":"https://doi.org/10.1109/icc52391.2025.11161856","title":"MAP Estimation-Based Device Activity Detection for Massive Grant-Free Access with Unknown Device Activity Probabilities","display_name":"MAP Estimation-Based Device Activity Detection for Massive Grant-Free Access with Unknown Device Activity Probabilities","publication_year":2025,"publication_date":"2025-06-08","ids":{"openalex":"https://openalex.org/W4414539063","doi":"https://doi.org/10.1109/icc52391.2025.11161856"},"language":"en","primary_location":{"id":"doi:10.1109/icc52391.2025.11161856","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc52391.2025.11161856","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2025 - IEEE International Conference on Communications","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/A5111793206","display_name":"Chuhan Jiang","orcid":"https://orcid.org/0000-0003-4862-2151"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chuhan Jiang","raw_affiliation_strings":["Shanghai Jiao Tong University,China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071987706","display_name":"Ying Cui","orcid":"https://orcid.org/0000-0003-3181-9775"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ying Cui","raw_affiliation_strings":["The Hong Kong University of Science and Technology,Guangzhou,China"],"affiliations":[{"raw_affiliation_string":"The Hong Kong University of Science and Technology,Guangzhou,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107171884","display_name":"Wang Liu","orcid":"https://orcid.org/0009-0003-5702-488X"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wang Liu","raw_affiliation_strings":["Shanghai Jiao Tong University,China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079652211","display_name":"Lianghui Ding","orcid":"https://orcid.org/0000-0002-3231-3613"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lianghui Ding","raw_affiliation_strings":["Shanghai Jiao Tong University,China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101807552","display_name":"Feng Yang","orcid":"https://orcid.org/0000-0002-6350-5765"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Yang","raw_affiliation_strings":["Shanghai Jiao Tong University,China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5111793206"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.2993371,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4233","last_page":"4238"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13553","display_name":"Age of Information Optimization","score":0.9646000266075134,"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/T13553","display_name":"Age of Information Optimization","score":0.9646000266075134,"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.95169997215271,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"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/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9326000213623047,"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/coordinate-descent","display_name":"Coordinate descent","score":0.6097000241279602},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5920000076293945},{"id":"https://openalex.org/keywords/equivalence","display_name":"Equivalence (formal languages)","score":0.5285000205039978},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.525600016117096},{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.43779999017715454},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.40310001373291016},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.4020000100135803},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.3361000120639801}],"concepts":[{"id":"https://openalex.org/C157553263","wikidata":"https://www.wikidata.org/wiki/Q5168004","display_name":"Coordinate descent","level":2,"score":0.6097000241279602},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5920000076293945},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5691999793052673},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5593000054359436},{"id":"https://openalex.org/C2780069185","wikidata":"https://www.wikidata.org/wiki/Q7977945","display_name":"Equivalence (formal languages)","level":2,"score":0.5285000205039978},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.525600016117096},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.43779999017715454},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.40310001373291016},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.4020000100135803},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36079999804496765},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.3361000120639801},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3359000086784363},{"id":"https://openalex.org/C2988656282","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity detection","level":2,"score":0.31380000710487366},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.29490000009536743},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.28610000014305115},{"id":"https://openalex.org/C68022304","wikidata":"https://www.wikidata.org/wiki/Q842217","display_name":"Bayes estimator","level":3,"score":0.28029999136924744},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.2775000035762787},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.27639999985694885},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.26829999685287476},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.2680000066757202},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.26350000500679016},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2623000144958496},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.26170000433921814},{"id":"https://openalex.org/C9810830","wikidata":"https://www.wikidata.org/wiki/Q635384","display_name":"Maximum a posteriori estimation","level":3,"score":0.2547000050544739},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.25}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icc52391.2025.11161856","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc52391.2025.11161856","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2025 - IEEE International Conference on Communications","raw_type":"proceedings-article"},{"id":"pmh:oai:repository.hkust.edu.hk:1783.1-166460","is_oa":false,"landing_page_url":"http://repository.hkust.edu.hk/ir/Record/1783.1-166460","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3549206154","display_name":null,"funder_award_id":"2023A03J0011,024A03J0623","funder_id":"https://openalex.org/F4320335480","funder_display_name":"Guangzhou Municipal Science and Technology Project"},{"id":"https://openalex.org/G6119235927","display_name":null,"funder_award_id":"62371412","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335480","display_name":"Guangzhou Municipal Science and Technology Project","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W631335369","https://openalex.org/W2150166076","https://openalex.org/W2706056020","https://openalex.org/W2961179947","https://openalex.org/W2981917204","https://openalex.org/W3001370401","https://openalex.org/W3036925027","https://openalex.org/W3212673851","https://openalex.org/W4220828397","https://openalex.org/W4249446031","https://openalex.org/W4312305043","https://openalex.org/W4391164391"],"related_works":[],"abstract_inverted_index":{"For":[0,70],"massive":[1],"grant-free":[2],"access,":[3],"maximum":[4],"a":[5,65,96,120],"posterior":[6],"(MAP)":[7],"estimation-based":[8,45],"device":[9,46,61,88,133],"activity":[10,24,39,47,91,134],"detection":[11,17,48,122,135],"is":[12,64],"known":[13,23],"to":[14,82,102],"achieve":[15],"superior":[16,121],"accuracy":[18,123],"in":[19,34,49],"the":[20,35,55,83,104,116,131],"scenario":[21,36],"of":[22,37,87],"probabilities.":[25,40,92],"Unfortunately,":[26],"no":[27],"comparable":[28],"Bayesian":[29],"statistical":[30],"estimation":[31,58,85,107],"method":[32],"exists":[33],"unknown":[38],"This":[41],"paper":[42],"investigates":[43],"MAP":[44,57,84,106],"this":[50],"scenario.":[51],"First,":[52],"we":[53,72,94,112],"formulate":[54],"hierarchical":[56],"problem":[59,77,86],"for":[60],"activities,":[62],"which":[63],"very":[66],"challenging":[67],"non-convex":[68,76],"problem.":[69],"tractability,":[71],"obtain":[73,103],"its":[74,80],"approximate":[75,105],"and":[78,90,124],"prove":[79],"equivalence":[81],"activities":[89],"Next,":[93],"propose":[95],"block":[97],"coordinate":[98],"descent":[99],"(BCD)-based":[100],"algorithm":[101,118],"problem's":[108],"stationary":[109],"points.":[110],"Finally,":[111],"numerically":[113],"show":[114],"that":[115],"proposed":[117],"achieves":[119],"short":[125],"computation":[126],"time":[127],"tradeoff":[128],"compared":[129],"with":[130],"state-of-the-art":[132],"methods.":[136]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}