{"id":"https://openalex.org/W4414646810","doi":"https://doi.org/10.1109/vtc2025-spring65109.2025.11174396","title":"A Channel Robust RFF Extraction Method Based on 802.11N HT-MF Preamble","display_name":"A Channel Robust RFF Extraction Method Based on 802.11N HT-MF Preamble","publication_year":2025,"publication_date":"2025-06-17","ids":{"openalex":"https://openalex.org/W4414646810","doi":"https://doi.org/10.1109/vtc2025-spring65109.2025.11174396"},"language":"en","primary_location":{"id":"doi:10.1109/vtc2025-spring65109.2025.11174396","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtc2025-spring65109.2025.11174396","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 101st Vehicular Technology Conference (VTC2025-Spring)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100408802","display_name":"Long Li","orcid":"https://orcid.org/0000-0003-1973-8550"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Long Li","raw_affiliation_strings":["School of Cyber Science and Engineering, Southeast University,Nanjing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Cyber Science and Engineering, Southeast University,Nanjing,China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016758631","display_name":"Yuan Zhong","orcid":"https://orcid.org/0000-0002-7503-1659"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Zhong","raw_affiliation_strings":["School of Cyber Science and Engineering, Southeast University,Nanjing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Cyber Science and Engineering, Southeast University,Nanjing,China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058074165","display_name":"Xuan Yang","orcid":"https://orcid.org/0000-0002-0666-6941"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuan Yang","raw_affiliation_strings":["School of Cyber Science and Engineering, Southeast University,Nanjing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Cyber Science and Engineering, Southeast University,Nanjing,China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018759775","display_name":"Fan Xiao","orcid":null},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fan Xiao","raw_affiliation_strings":["School of Cyber Science and Engineering, Southeast University,Nanjing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Cyber Science and Engineering, Southeast University,Nanjing,China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100759528","display_name":"Dongming Li","orcid":"https://orcid.org/0000-0002-4557-6279"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongming Li","raw_affiliation_strings":["School of Cyber Science and Engineering, Southeast University,Nanjing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Cyber Science and Engineering, Southeast University,Nanjing,China","institution_ids":["https://openalex.org/I76569877"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I76569877"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12791","display_name":"Full-Duplex Wireless Communications","score":0.9769999980926514,"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"}},"topics":[{"id":"https://openalex.org/T12791","display_name":"Full-Duplex Wireless Communications","score":0.9769999980926514,"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/T10575","display_name":"Wireless Communication Networks Research","score":0.9610000252723694,"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9326000213623047,"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/preamble","display_name":"Preamble","score":0.9398000240325928},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.6327999830245972},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.620199978351593},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.5856000185012817},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.48750001192092896},{"id":"https://openalex.org/keywords/fingerprint","display_name":"Fingerprint (computing)","score":0.47510001063346863},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47049999237060547},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.444599986076355},{"id":"https://openalex.org/keywords/radio-frequency-identification","display_name":"Radio-frequency identification","score":0.4214000105857849}],"concepts":[{"id":"https://openalex.org/C2780691134","wikidata":"https://www.wikidata.org/wiki/Q1129448","display_name":"Preamble","level":3,"score":0.9398000240325928},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.6327999830245972},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.620199978351593},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.5856000185012817},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5557000041007996},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.48750001192092896},{"id":"https://openalex.org/C2777826928","wikidata":"https://www.wikidata.org/wiki/Q3745713","display_name":"Fingerprint (computing)","level":2,"score":0.47510001063346863},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47049999237060547},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.444599986076355},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43630000948905945},{"id":"https://openalex.org/C204222849","wikidata":"https://www.wikidata.org/wiki/Q104954","display_name":"Radio-frequency identification","level":2,"score":0.4214000105857849},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4025999903678894},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.34880000352859497},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.34850001335144043},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.3456000089645386},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3450999855995178},{"id":"https://openalex.org/C168406668","wikidata":"https://www.wikidata.org/wiki/Q178022","display_name":"Fingerprint recognition","level":3,"score":0.3402999937534332},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3328999876976013},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.3125999867916107},{"id":"https://openalex.org/C40409654","wikidata":"https://www.wikidata.org/wiki/Q375889","display_name":"Orthogonal frequency-division multiplexing","level":3,"score":0.30489999055862427},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.2989000082015991},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2904999852180481},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.2896000146865845},{"id":"https://openalex.org/C74064498","wikidata":"https://www.wikidata.org/wiki/Q3396184","display_name":"Radio frequency","level":2,"score":0.28949999809265137},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2870999872684479},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.2858000099658966},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.28380000591278076},{"id":"https://openalex.org/C103088060","wikidata":"https://www.wikidata.org/wiki/Q1062839","display_name":"Error detection and correction","level":2,"score":0.28360000252723694},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.27469998598098755},{"id":"https://openalex.org/C2778562939","wikidata":"https://www.wikidata.org/wiki/Q1298791","display_name":"Synchronization (alternating current)","level":3,"score":0.25130000710487366}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vtc2025-spring65109.2025.11174396","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtc2025-spring65109.2025.11174396","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 101st Vehicular Technology Conference (VTC2025-Spring)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2966736488","https://openalex.org/W3047279638","https://openalex.org/W4312681730","https://openalex.org/W4387444497","https://openalex.org/W4387987100","https://openalex.org/W4389723693","https://openalex.org/W4391496465","https://openalex.org/W4394712820","https://openalex.org/W4399074069","https://openalex.org/W4399877772","https://openalex.org/W4400277665","https://openalex.org/W4402811033","https://openalex.org/W4403052684"],"related_works":[],"abstract_inverted_index":{"In":[0],"the":[1,13,25,36,57,61,74,82,91,98,125,130,138,142,151],"research":[2],"of":[3,17,60,93,214],"Wi-Fi":[4,50,161],"device":[5],"identification,":[6],"Radio":[7],"Frequency":[8],"Fingerprint":[9],"(RFF)":[10],"identification":[11,30],"leverages":[12],"inherent":[14],"hardware":[15],"characteristics":[16,149],"devices":[18,162],"to":[19,33,119,175,198],"establish":[20],"a":[21,188,209],"unique":[22],"identity":[23],"at":[24],"physical":[26],"layer.":[27],"However,":[28],"RFF":[29,45],"is":[31,116],"vulnerable":[32],"variations":[34],"in":[35,66,97,141,191],"wireless":[37],"channel.":[38],"Although":[39],"several":[40],"studies":[41],"have":[42],"proposed":[43],"channel-robust":[44],"extraction":[46],"methods":[47,176],"based":[48],"on":[49,56,159],"signal":[51],"preambles,":[52],"these":[53],"approaches":[54],"rely":[55],"legacy":[58],"preamble":[59,80,144],"802.11":[62],"protocol,":[63],"which":[64],"results":[65],"relatively":[67],"limited":[68],"feature":[69,113],"dimensions.":[70],"This":[71,133],"paper":[72,134],"introduces":[73],"High":[75],"Throughput":[76],"Mixed":[77],"Format":[78],"(HT-MF)":[79],"under":[81],"802.11n":[83],"protocol":[84],"framework,":[85],"removing":[86],"channel":[87,147,165,178,185,200],"effects":[88],"by":[89],"calculating":[90],"ratio":[92],"three":[94,139],"independent":[95],"symbols":[96,140],"frequency":[99],"domain":[100],"and":[101,123,170],"subsequently":[102],"extracting":[103],"24-dimensional":[104],"RF":[105],"fingerprint":[106],"features.":[107],"Maximum":[108],"relevance":[109],"minimum":[110],"redundancy":[111],"(MRMR)":[112],"selection":[114],"algorithm":[115],"then":[117],"applied":[118],"remove":[120],"redundant":[121],"features":[122],"retain":[124],"most":[126],"discriminative":[127],"ones":[128],"for":[129],"final":[131],"RFF.":[132],"analytically":[135],"shows":[136,205],"that":[137],"HTMF":[143],"exhibit":[145],"similar":[146],"response":[148],"within":[150],"channel's":[152],"coherence":[153],"time.":[154],"We":[155],"conducted":[156],"extensive":[157],"experiments":[158],"eight":[160],"across":[163],"multiple":[164],"environments,":[166],"including":[167],"four":[168],"static":[169],"one":[171],"dynamic":[172],"scenario.":[173],"Compared":[174],"without":[177],"effect":[179],"mitigation,":[180],"our":[181,203],"approach":[182,204],"significantly":[183],"improves":[184],"robustness,":[186],"achieving":[187],"45.2%":[189],"increase":[190],"average":[192],"recognition":[193,211],"accuracy.":[194],"Additionally,":[195],"when":[196],"compared":[197],"other":[199],"mitigation":[201],"methods,":[202],"superior":[206],"performance,":[207],"with":[208],"maximum":[210],"accuracy":[212],"improvement":[213],"20.2%.":[215]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}