{"id":"https://openalex.org/W4386360598","doi":"https://doi.org/10.1109/icccworkshops57813.2023.10233803","title":"ReCPos: Deep Learning Network for 5G NR High-precision Positioning","display_name":"ReCPos: Deep Learning Network for 5G NR High-precision Positioning","publication_year":2023,"publication_date":"2023-08-10","ids":{"openalex":"https://openalex.org/W4386360598","doi":"https://doi.org/10.1109/icccworkshops57813.2023.10233803"},"language":"en","primary_location":{"id":"doi:10.1109/icccworkshops57813.2023.10233803","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icccworkshops57813.2023.10233803","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/CIC International Conference on Communications in China (ICCC Workshops)","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/A5019619018","display_name":"Fangyi Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Fangyi Yu","raw_affiliation_strings":["Beijing University of Posts and Telecommunications (BUPT),Beijing,China","Beijing University of Posts and Telecommunications (BUPT), Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications (BUPT),Beijing,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Beijing University of Posts and Telecommunications (BUPT), Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101624672","display_name":"Long Zhao","orcid":"https://orcid.org/0000-0001-5839-8005"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Long Zhao","raw_affiliation_strings":["Beijing University of Posts and Telecommunications (BUPT),Beijing,China","Beijing University of Posts and Telecommunications (BUPT), Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications (BUPT),Beijing,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Beijing University of Posts and Telecommunications (BUPT), Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040176629","display_name":"Xinfang Chen","orcid":"https://orcid.org/0000-0001-6899-5858"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinfang Chen","raw_affiliation_strings":["Beijing University of Posts and Telecommunications (BUPT),Beijing,China","Beijing University of Posts and Telecommunications (BUPT), Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications (BUPT),Beijing,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Beijing University of Posts and Telecommunications (BUPT), Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048072437","display_name":"Hongrui Shen","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongrui Shen","raw_affiliation_strings":["Beijing University of Posts and Telecommunications (BUPT),Beijing,China","Beijing University of Posts and Telecommunications (BUPT), Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications (BUPT),Beijing,China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Beijing University of Posts and Telecommunications (BUPT), Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5019619018"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.2674,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.53794323,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":1.0,"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":1.0,"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/T11192","display_name":"Underwater Vehicles and Communication Systems","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9926999807357788,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/non-line-of-sight-propagation","display_name":"Non-line-of-sight propagation","score":0.8994655013084412},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.8056106567382812},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.769333004951477},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.5894387364387512},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.45948442816734314},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.4496600031852722},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4454942047595978},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43078213930130005},{"id":"https://openalex.org/keywords/hybrid-positioning-system","display_name":"Hybrid positioning system","score":0.4142783284187317},{"id":"https://openalex.org/keywords/positioning-system","display_name":"Positioning system","score":0.35603898763656616},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.23611867427825928},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.22680720686912537},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.21518269181251526},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.204437255859375}],"concepts":[{"id":"https://openalex.org/C154910267","wikidata":"https://www.wikidata.org/wiki/Q1740982","display_name":"Non-line-of-sight propagation","level":3,"score":0.8994655013084412},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.8056106567382812},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.769333004951477},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.5894387364387512},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.45948442816734314},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4496600031852722},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4454942047595978},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43078213930130005},{"id":"https://openalex.org/C187394410","wikidata":"https://www.wikidata.org/wiki/Q17141406","display_name":"Hybrid positioning system","level":4,"score":0.4142783284187317},{"id":"https://openalex.org/C2778603505","wikidata":"https://www.wikidata.org/wiki/Q17141406","display_name":"Positioning system","level":3,"score":0.35603898763656616},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.23611867427825928},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.22680720686912537},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.21518269181251526},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.204437255859375},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icccworkshops57813.2023.10233803","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icccworkshops57813.2023.10233803","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/CIC International Conference on Communications in China (ICCC Workshops)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.5}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2120350100","https://openalex.org/W2194775991","https://openalex.org/W2240192984","https://openalex.org/W2309512289","https://openalex.org/W2739582838","https://openalex.org/W2781561575","https://openalex.org/W2946902499","https://openalex.org/W3056919267","https://openalex.org/W3108914020","https://openalex.org/W3133300446","https://openalex.org/W4210901908"],"related_works":["https://openalex.org/W2338366266","https://openalex.org/W189713034","https://openalex.org/W2171782134","https://openalex.org/W2755401669","https://openalex.org/W2373655383","https://openalex.org/W2226364097","https://openalex.org/W2376506503","https://openalex.org/W4386858421","https://openalex.org/W2124945426","https://openalex.org/W2552390423"],"abstract_inverted_index":{"With":[0],"the":[1,14,22,64,67,78,86,91,97,105,110,119],"increasing":[2],"demand":[3],"for":[4,47,66],"location-based":[5],"services,":[6],"various":[7],"positioning":[8,16,49,111,122,153],"technologies":[9,17],"have":[10],"been":[11],"proposed.":[12],"However,":[13],"existing":[15,120],"are":[18,61,82],"often":[19],"limited":[20],"to":[21,84,118],"line-of-sight":[23],"(LOS)":[24],"scenario":[25],"and":[26,72,132,142],"incapable":[27],"of":[28,137,147,152],"providing":[29],"accurate":[30],"results":[31,102],"under":[32],"non-LoS":[33],"(NLOS)":[34],"scenario.":[35],"Therefore,":[36],"we":[37],"propose":[38],"ReCPos":[39,98,107],"net,":[40],"a":[41],"deep":[42],"residual":[43,56,80],"convolutional":[44],"neural":[45],"network":[46],"high-precision":[48],"in":[50,124,150],"heavy":[51,125],"NLOS":[52,126],"scenario,":[53],"where":[54],"four":[55],"modules":[57,81],"with":[58,128,140],"distinct":[59],"structures":[60],"designed.":[62],"After":[63],"preprocessing":[65],"channel":[68],"impulse":[69],"response":[70],"(CIR)":[71],"reference":[73],"signal":[74],"received":[75],"power":[76],"(RSRP),":[77],"designed":[79],"adopted":[83],"extract":[85],"high-dimensional":[87],"feature":[88],"vector,":[89],"then":[90],"location":[92],"can":[93],"be":[94],"predicted":[95],"by":[96,113],"net.":[99],"The":[100,135],"experiment":[101],"indicate":[103],"that":[104,146],"proposed":[106],"could":[108],"reduce":[109],"error":[112],"at":[114],"least":[115],"20.0%":[116],"compared":[117],"AI-based":[121],"schemes":[123],"conditions":[127],"lower":[129],"model":[130],"complexity":[131],"computing":[133],"power.":[134],"input":[136],"CIR":[138,144,148],"combined":[139],"RSRP":[141],"truncating":[143],"outperforms":[145],"alone":[149],"terms":[151],"accuracy.":[154]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
