{"id":"https://openalex.org/W2967458456","doi":"https://doi.org/10.1109/jsac.2019.2933779","title":"Sparsely Self-Supervised Generative Adversarial Nets for Radio Frequency Estimation","display_name":"Sparsely Self-Supervised Generative Adversarial Nets for Radio Frequency Estimation","publication_year":2019,"publication_date":"2019-08-13","ids":{"openalex":"https://openalex.org/W2967458456","doi":"https://doi.org/10.1109/jsac.2019.2933779","mag":"2967458456"},"language":"en","primary_location":{"id":"doi:10.1109/jsac.2019.2933779","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jsac.2019.2933779","pdf_url":null,"source":{"id":"https://openalex.org/S90422530","display_name":"IEEE Journal on Selected Areas in Communications","issn_l":"0733-8716","issn":["0733-8716","1558-0008"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal on Selected Areas in Communications","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/A5101467444","display_name":"Zhuo Li","orcid":"https://orcid.org/0000-0002-2141-788X"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":true,"raw_author_name":"Zhuo Li","raw_affiliation_strings":["Department of Computing, The Hong Kong Polytechnic University, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Computing, The Hong Kong Polytechnic University, Hong Kong","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100740023","display_name":"Jiannong Cao","orcid":"https://orcid.org/0000-0002-2725-2529"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Jiannong Cao","raw_affiliation_strings":["Department of Computing, The Hong Kong Polytechnic University, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Computing, The Hong Kong Polytechnic University, Hong Kong","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100357128","display_name":"Hongwei Wang","orcid":"https://orcid.org/0000-0001-7474-8271"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hongwei Wang","raw_affiliation_strings":["Department of Computer Science, Stanford University, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Stanford University, CA, USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074355807","display_name":"Miao Zhao","orcid":"https://orcid.org/0000-0002-4324-1467"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Miao Zhao","raw_affiliation_strings":["Department of Computing, The Hong Kong Polytechnic University, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Computing, The Hong Kong Polytechnic University, Hong Kong","institution_ids":["https://openalex.org/I14243506"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101467444"],"corresponding_institution_ids":["https://openalex.org/I14243506"],"apc_list":null,"apc_paid":null,"fwci":1.5918,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.87851016,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"37","issue":"11","first_page":"2428","last_page":"2442"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.975600004196167,"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":0.975600004196167,"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/T10515","display_name":"Cancer-related molecular mechanisms research","score":0.9642999768257141,"subfield":{"id":"https://openalex.org/subfields/1306","display_name":"Cancer Research"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9598000049591064,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/discriminator","display_name":"Discriminator","score":0.9307780265808105},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7938662767410278},{"id":"https://openalex.org/keywords/radio-frequency","display_name":"Radio frequency","score":0.6900177597999573},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.6515534520149231},{"id":"https://openalex.org/keywords/minimax","display_name":"Minimax","score":0.4767400026321411},{"id":"https://openalex.org/keywords/interference","display_name":"Interference (communication)","score":0.42331695556640625},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.412862092256546},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3558693528175354},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3347761034965515},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.26176783442497253},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.20777899026870728},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1291256844997406},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.1081407368183136},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.09520062804222107},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.08846533298492432},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.08694899082183838}],"concepts":[{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.9307780265808105},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7938662767410278},{"id":"https://openalex.org/C74064498","wikidata":"https://www.wikidata.org/wiki/Q3396184","display_name":"Radio frequency","level":2,"score":0.6900177597999573},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.6515534520149231},{"id":"https://openalex.org/C149728462","wikidata":"https://www.wikidata.org/wiki/Q751319","display_name":"Minimax","level":2,"score":0.4767400026321411},{"id":"https://openalex.org/C32022120","wikidata":"https://www.wikidata.org/wiki/Q797225","display_name":"Interference (communication)","level":3,"score":0.42331695556640625},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.412862092256546},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3558693528175354},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3347761034965515},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.26176783442497253},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.20777899026870728},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1291256844997406},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.1081407368183136},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.09520062804222107},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.08846533298492432},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.08694899082183838},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jsac.2019.2933779","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jsac.2019.2933779","pdf_url":null,"source":{"id":"https://openalex.org/S90422530","display_name":"IEEE Journal on Selected Areas in Communications","issn_l":"0733-8716","issn":["0733-8716","1558-0008"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal on Selected Areas in Communications","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6800000071525574,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G331123893","display_name":null,"funder_award_id":"2018YFB1004801","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":70,"referenced_works":["https://openalex.org/W648143168","https://openalex.org/W1507700505","https://openalex.org/W1518434439","https://openalex.org/W1522301498","https://openalex.org/W1533861849","https://openalex.org/W1536680647","https://openalex.org/W1665214252","https://openalex.org/W1745334888","https://openalex.org/W1815076433","https://openalex.org/W1836465849","https://openalex.org/W1959608418","https://openalex.org/W1985258161","https://openalex.org/W2054405892","https://openalex.org/W2060204507","https://openalex.org/W2061992737","https://openalex.org/W2085468792","https://openalex.org/W2099471712","https://openalex.org/W2101926813","https://openalex.org/W2103972604","https://openalex.org/W2107878631","https://openalex.org/W2108598243","https://openalex.org/W2125389028","https://openalex.org/W2141200610","https://openalex.org/W2147800946","https://openalex.org/W2163605009","https://openalex.org/W2164679141","https://openalex.org/W2194775991","https://openalex.org/W2267126114","https://openalex.org/W2273972066","https://openalex.org/W2293078015","https://openalex.org/W2395591486","https://openalex.org/W2423557781","https://openalex.org/W2520164769","https://openalex.org/W2611104282","https://openalex.org/W2613718673","https://openalex.org/W2739748921","https://openalex.org/W2951523806","https://openalex.org/W2953106684","https://openalex.org/W2953318193","https://openalex.org/W2963073614","https://openalex.org/W2963226019","https://openalex.org/W2963373786","https://openalex.org/W2963420272","https://openalex.org/W2963636093","https://openalex.org/W2963684088","https://openalex.org/W2963917315","https://openalex.org/W2964046669","https://openalex.org/W2964121744","https://openalex.org/W3147022770","https://openalex.org/W4238530616","https://openalex.org/W4302061398","https://openalex.org/W4320013936","https://openalex.org/W6620707391","https://openalex.org/W6621378261","https://openalex.org/W6631101137","https://openalex.org/W6631190155","https://openalex.org/W6631943919","https://openalex.org/W6637242042","https://openalex.org/W6638545294","https://openalex.org/W6638667902","https://openalex.org/W6640963894","https://openalex.org/W6678815747","https://openalex.org/W6684191040","https://openalex.org/W6685352114","https://openalex.org/W6694605516","https://openalex.org/W6712291075","https://openalex.org/W6718140377","https://openalex.org/W6718379498","https://openalex.org/W6726381175","https://openalex.org/W6741832134"],"related_works":["https://openalex.org/W2953246223","https://openalex.org/W4293320219","https://openalex.org/W3110074278","https://openalex.org/W4283584549","https://openalex.org/W2618858825","https://openalex.org/W2554314924","https://openalex.org/W2998859928","https://openalex.org/W3156863413","https://openalex.org/W4381885966","https://openalex.org/W4288256692"],"abstract_inverted_index":{"Radio":[0],"frequency":[1],"(RF)":[2],"estimation":[3,19,224,268],"plays":[4],"a":[5,47,135,159,190,214,246,256],"significant":[6],"role":[7],"in":[8,101],"cellular":[9],"network's":[10],"planning":[11],"and":[12,32,107,153,282],"optimization.":[13],"The":[14],"conventional":[15],"methods":[16],"for":[17,245],"RF":[18,54,123,151,154,182,220],"are":[20,276],"mainly":[21],"based":[22],"on":[23,126,217,255],"radio":[24],"propagation":[25],"models,":[26],"which":[27,210],"suffer":[28],"from":[29,36,59,93,97,120],"low":[30],"accuracy":[31,269],"coarse":[33],"granularity.":[34],"Distinguished":[35],"existing":[37],"methods,":[38],"we":[39],"propose":[40],"sparsely":[41,232],"self-supervised":[42,233],"generative":[43],"adversarial":[44,208],"nets":[45],"(SS-GAN),":[46],"novel":[48],"data-driven":[49],"model":[50,247],"to":[51,111,139,146,172,178,197,212,223],"generate":[52],"the":[53,67,72,75,81,84,89,102,116,121,129,141,149,173,181,187,198,207,218,239,242,267,271],"maps":[55,221],"of":[56,77,83,128,137,148,161,201,241],"an":[57,230],"area":[58],"irregularly":[60],"distributed":[61],"measurement":[62],"samples.":[63],"SS-GAN":[64,132,156,202,228,263],"meticulously":[65],"adopts":[66],"standard":[68],"GAN":[69,130,174],"framework,":[70,131],"where":[71],"generator":[73,106,117],"learns":[74],"distribution":[76],"true":[78,122],"observations":[79,147],"under":[80],"guidance":[82],"discriminator":[85,108],"that":[86,237,262],"discriminates":[87],"whether":[88],"input":[90,170],"data":[91],"is":[92,118,195],"real":[94],"samples":[95],"or":[96],"generated":[98,219],"outputs.":[99],"Competition":[100],"minmax":[103],"game":[104],"between":[105],"drives":[109],"them":[110],"improve":[112,266],"their":[113],"capability,":[114],"until":[115],"indistinguishable":[119],"distribution.":[124],"Specifically,":[125],"top":[127],"carries":[133],"out":[134],"variety":[136],"operations":[138],"enhance":[140],"estimation:":[142],"(1)":[143],"In":[144],"addition":[145],"measured":[150],"coverage":[152],"interference,":[155],"also":[157],"employs":[158],"collection":[160],"crucial":[162],"auxiliary":[163],"information":[164],"(e.g.,":[165],"geographic":[166],"data)":[167],"as":[168,177],"additional":[169],"features":[171],"framework":[175],"so":[176],"precisely":[179],"characterize":[180],"environment;":[183],"(2)":[184],"To":[185],"dampen":[186],"training":[188],"instability,":[189],"new":[191],"lightweight":[192],"reconstruction":[193],"loss":[194],"introduced":[196],"objective":[199],"function":[200],"rather":[203],"than":[204],"solely":[205],"using":[206],"loss,":[209],"aims":[211],"impose":[213],"weak":[215],"supervision":[216],"according":[222],"accuracy;":[225],"(3)":[226],"Moreover,":[227],"designs":[229],"innovative":[231],"(SS)":[234],"learning":[235],"mechanism":[236],"facilitates":[238],"validation":[240],"estimated":[243],"results":[244,275],"lacking":[248],"direct":[249],"ground":[250],"truth":[251],"knowledge.":[252],"Extensive":[253],"experiments":[254],"real-world":[257],"4G":[258],"LTE":[259],"dataset":[260],"demonstrate":[261],"can":[264],"substantially":[265],"over":[270],"state-of-the-art":[272],"baselines.":[273],"Comparison":[274],"presented":[277],"through":[278],"visualized":[279],"case":[280],"studies":[281],"quantitative":[283],"statistics.":[284]},"counts_by_year":[{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
