{"id":"https://openalex.org/W4417282335","doi":"https://doi.org/10.1109/pimrc62392.2025.11275042","title":"Scenario Diversity Assessment for Data Down Scaling in Wireless AI: a Geometric Feature-Based Approach","display_name":"Scenario Diversity Assessment for Data Down Scaling in Wireless AI: a Geometric Feature-Based Approach","publication_year":2025,"publication_date":"2025-09-01","ids":{"openalex":"https://openalex.org/W4417282335","doi":"https://doi.org/10.1109/pimrc62392.2025.11275042"},"language":null,"primary_location":{"id":"doi:10.1109/pimrc62392.2025.11275042","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pimrc62392.2025.11275042","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 36th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)","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/A5054280305","display_name":"Ridong Li","orcid":"https://orcid.org/0000-0001-6988-8894"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ridong Li","raw_affiliation_strings":["Zhejiang University,College of Information Science and Electronic Engineering,Hangzhou,China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University,College of Information Science and Electronic Engineering,Hangzhou,China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106695884","display_name":"Zhaoyang Zhang","orcid":"https://orcid.org/0009-0002-5802-5027"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaoyang Zhang","raw_affiliation_strings":["Zhejiang University,College of Information Science and Electronic Engineering,Hangzhou,China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University,College of Information Science and Electronic Engineering,Hangzhou,China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069404551","display_name":"Zirui Chen","orcid":"https://orcid.org/0009-0009-3748-2211"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zirui Chen","raw_affiliation_strings":["Zhejiang University,College of Information Science and Electronic Engineering,Hangzhou,China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University,College of Information Science and Electronic Engineering,Hangzhou,China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066878475","display_name":"Zhaohui Yang","orcid":"https://orcid.org/0000-0002-4475-589X"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaohui Yang","raw_affiliation_strings":["Zhejiang University,College of Information Science and Electronic Engineering,Hangzhou,China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University,College of Information Science and Electronic Engineering,Hangzhou,China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070646892","display_name":"Richeng Jin","orcid":"https://orcid.org/0000-0002-1480-585X"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Richeng Jin","raw_affiliation_strings":["Zhejiang University,College of Information Science and Electronic Engineering,Hangzhou,China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University,College of Information Science and Electronic Engineering,Hangzhou,China","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5054280305"],"corresponding_institution_ids":["https://openalex.org/I76130692"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20858345,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"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/T12131","display_name":"Wireless Signal Modulation Classification","score":0.21940000355243683,"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":0.21940000355243683,"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.14069999754428864,"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/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.13040000200271606,"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/generalization","display_name":"Generalization","score":0.741100013256073},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6823999881744385},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.602400004863739},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.5268999934196472},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.48989999294281006},{"id":"https://openalex.org/keywords/wireless-sensor-network","display_name":"Wireless sensor network","score":0.4447999894618988},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.44179999828338623},{"id":"https://openalex.org/keywords/wireless-network","display_name":"Wireless network","score":0.4392000138759613},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.36649999022483826}],"concepts":[{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.741100013256073},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6823999881744385},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6599000096321106},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6230000257492065},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.602400004863739},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.5268999934196472},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.48989999294281006},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.4447999894618988},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.44179999828338623},{"id":"https://openalex.org/C108037233","wikidata":"https://www.wikidata.org/wiki/Q11375","display_name":"Wireless network","level":3,"score":0.4392000138759613},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.36649999022483826},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.366100013256073},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.3416000008583069},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.3262999951839447},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3181000053882599},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3179999887943268},{"id":"https://openalex.org/C91682802","wikidata":"https://www.wikidata.org/wiki/Q620538","display_name":"Multidimensional scaling","level":2,"score":0.31349998712539673},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30880001187324524},{"id":"https://openalex.org/C136817519","wikidata":"https://www.wikidata.org/wiki/Q947493","display_name":"Diversity combining","level":4,"score":0.3077999949455261},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.30300000309944153},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.30140000581741333},{"id":"https://openalex.org/C81978471","wikidata":"https://www.wikidata.org/wiki/Q1196572","display_name":"Fading","level":3,"score":0.2741999924182892},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.27379998564720154},{"id":"https://openalex.org/C143271835","wikidata":"https://www.wikidata.org/wiki/Q254515","display_name":"Similitude","level":2,"score":0.26669999957084656},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.25769999623298645},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.25049999356269836}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/pimrc62392.2025.11275042","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pimrc62392.2025.11275042","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 36th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2963889719","https://openalex.org/W3123490382","https://openalex.org/W4233762729","https://openalex.org/W4312398637","https://openalex.org/W4387805535","https://openalex.org/W4390660070","https://openalex.org/W4392152176","https://openalex.org/W4400188118","https://openalex.org/W4401508981","https://openalex.org/W4401878796","https://openalex.org/W4409156697","https://openalex.org/W4411609169"],"related_works":[],"abstract_inverted_index":{"Generalization":[0],"from":[1,57],"a":[2,76,152,170],"specific":[3],"scenario":[4,80],"to":[5,65,85,105,118,131,150],"the":[6,39,68,87,107,125,133,165,184],"whole":[7],"network":[8],"is":[9,144],"of":[10,30],"particular":[11],"importance":[12],"in":[13,23,51],"wireless":[14,45,52],"artificial":[15],"intelligence,":[16],"which":[17],"usually":[18],"calls":[19],"for":[20,79,91,146,158],"scaling":[21],"up":[22],"training":[24,69,92],"data":[25,32,56,93],"and":[26,34,180],"brings":[27],"unaffordable":[28],"costs":[29],"both":[31],"collection":[33],"model":[35],"training.":[36],"Motivated":[37],"by":[38],"fact":[40],"that":[41,164],"local":[42],"similarity":[43,50,134],"among":[44],"scenarios":[46,59,90,149],"probably":[47],"means":[48],"certain":[49],"channel":[53],"characteristics,":[54],"collecting":[55],"representative":[58,89,148],"may":[60],"be":[61],"an":[62],"efficient":[63],"way":[64],"scale":[66],"down":[67],"dataset.":[70],"In":[71],"this":[72,96],"paper,":[73],"we":[74],"propose":[75],"proactive":[77],"approach":[78,97,167],"diversity":[81],"assessment":[82],"so":[83],"as":[84],"choose":[86],"most":[88],"collection.":[94],"Specifically,":[95],"first":[98],"utilizes":[99],"publicly":[100],"available":[101],"coarse":[102],"environmental":[103],"maps":[104],"extract":[106],"geometric":[108],"features,":[109],"then":[110],"combines":[111],"these":[112],"with":[113,124,155],"electromagnetic":[114,120,136],"signal":[115],"propagation":[116],"models":[117],"synthesize":[119],"characteristic":[121,137],"distributions":[122,138],"associated":[123],"scenario.":[126],"By":[127],"employing":[128],"Wasserstein":[129],"distance":[130],"quantify":[132],"between":[135],"across":[139],"different":[140],"scenarios,":[141],"scenario-granularity":[142],"clustering":[143],"achieved":[145],"selecting":[147],"construct":[151],"global":[153],"dataset":[154],"sufficient":[156],"information":[157],"all":[159],"scenarios.":[160],"Experimental":[161],"results":[162],"demonstrate":[163],"proposed":[166],"can":[168],"achieve":[169],"Pearson":[171],"correlation":[172],"coefficient":[173],"above":[174],"0.8":[175],"w.r.t.":[176],"cross-scenario":[177],"generalization":[178],"performance,":[179],"it":[181],"further":[182],"improves":[183],"final":[185],"multi-scenario":[186],"generalization,":[187],"surpassing":[188],"existing":[189],"methods":[190],"while":[191],"requiring":[192],"no":[193],"pre-measurement":[194],"data.":[195]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-12-12T00:00:00"}