{"id":"https://openalex.org/W7138838077","doi":"https://doi.org/10.1109/globecom59602.2025.11432134","title":"Beamforming-Codebook-Aware Channel Knowledge Map Construction for Multi-Antenna Systems","display_name":"Beamforming-Codebook-Aware Channel Knowledge Map Construction for Multi-Antenna Systems","publication_year":2025,"publication_date":"2025-12-08","ids":{"openalex":"https://openalex.org/W7138838077","doi":"https://doi.org/10.1109/globecom59602.2025.11432134"},"language":null,"primary_location":{"id":"doi:10.1109/globecom59602.2025.11432134","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom59602.2025.11432134","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2025 - 2025 IEEE Global Communications Conference","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":null,"display_name":"Haohan Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haohan Wang","raw_affiliation_strings":["Tsinghua University,Beijing National Research Center for Information Science and Technology (BNRist),Dept. of Electronic Engineering,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Beijing National Research Center for Information Science and Technology (BNRist),Dept. of Electronic Engineering,Beijing,China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005661563","display_name":"Xu Shi","orcid":"https://orcid.org/0000-0002-9478-1818"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Shi","raw_affiliation_strings":["Tsinghua University,Beijing National Research Center for Information Science and Technology (BNRist),Dept. of Electronic Engineering,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Beijing National Research Center for Information Science and Technology (BNRist),Dept. of Electronic Engineering,Beijing,China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100377411","display_name":"Hailong Zhang","orcid":"https://orcid.org/0000-0002-8951-7094"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hengyu Zhang","raw_affiliation_strings":["Tsinghua University,Beijing National Research Center for Information Science and Technology (BNRist),Dept. of Electronic Engineering,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Beijing National Research Center for Information Science and Technology (BNRist),Dept. of Electronic Engineering,Beijing,China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130006991","display_name":"Yashuai Cao","orcid":null},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yashuai Cao","raw_affiliation_strings":["University of Science and Technology,Dept. of Intelligence Science and Technology,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science and Technology,Dept. of Intelligence Science and Technology,Beijing,China","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5129823684","display_name":"Jintao Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jintao Wang","raw_affiliation_strings":["Tsinghua University,Beijing National Research Center for Information Science and Technology (BNRist),Dept. of Electronic Engineering,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Beijing National Research Center for Information Science and Technology (BNRist),Dept. of Electronic Engineering,Beijing,China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.59633379,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1471","last_page":"1476"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10936","display_name":"Millimeter-Wave Propagation and Modeling","score":0.7021999955177307,"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/T10936","display_name":"Millimeter-Wave Propagation and Modeling","score":0.7021999955177307,"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":0.09839999675750732,"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/T11458","display_name":"Advanced Wireless Communication Technologies","score":0.07039999961853027,"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/precoding","display_name":"Precoding","score":0.7616000175476074},{"id":"https://openalex.org/keywords/mimo","display_name":"MIMO","score":0.5515999794006348},{"id":"https://openalex.org/keywords/beamforming","display_name":"Beamforming","score":0.47780001163482666},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.43209999799728394},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4016999900341034},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.37860000133514404},{"id":"https://openalex.org/keywords/tracing","display_name":"Tracing","score":0.37290000915527344},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.3400999903678894},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.33980000019073486}],"concepts":[{"id":"https://openalex.org/C160562895","wikidata":"https://www.wikidata.org/wiki/Q7239557","display_name":"Precoding","level":4,"score":0.7616000175476074},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.701200008392334},{"id":"https://openalex.org/C207987634","wikidata":"https://www.wikidata.org/wiki/Q176862","display_name":"MIMO","level":3,"score":0.5515999794006348},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.5509999990463257},{"id":"https://openalex.org/C54197355","wikidata":"https://www.wikidata.org/wiki/Q5782992","display_name":"Beamforming","level":2,"score":0.47780001163482666},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.43209999799728394},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4235000014305115},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4016999900341034},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.3926999866962433},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3880000114440918},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.37860000133514404},{"id":"https://openalex.org/C138673069","wikidata":"https://www.wikidata.org/wiki/Q322229","display_name":"Tracing","level":2,"score":0.37290000915527344},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.3400999903678894},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.33980000019073486},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32919999957084656},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32510000467300415},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.3240000009536743},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3165000081062317},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.31200000643730164},{"id":"https://openalex.org/C57733114","wikidata":"https://www.wikidata.org/wiki/Q1006032","display_name":"Discrete Fourier transform (general)","level":5,"score":0.30889999866485596},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.30480000376701355},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.29789999127388},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.296999990940094},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.29499998688697815},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28769999742507935},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.2831000089645386},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.27149999141693115},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2630999982357025},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.2583000063896179},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.2572000026702881},{"id":"https://openalex.org/C67692717","wikidata":"https://www.wikidata.org/wiki/Q187444","display_name":"Low-density parity-check code","level":3,"score":0.25380000472068787},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.2506999969482422}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/globecom59602.2025.11432134","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom59602.2025.11432134","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2025 - 2025 IEEE Global Communications Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.5251548290252686,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1490921409","https://openalex.org/W2272804037","https://openalex.org/W3131967102","https://openalex.org/W4387430923","https://openalex.org/W4387730064","https://openalex.org/W4391697040","https://openalex.org/W4393028566","https://openalex.org/W4403125527","https://openalex.org/W4405232162","https://openalex.org/W4408145391","https://openalex.org/W4411949912"],"related_works":[],"abstract_inverted_index":{"Channel":[0],"knowledge":[1],"map":[2],"(CKM)":[3],"has":[4],"emerged":[5],"as":[6],"a":[7,94,113,121,147],"crucial":[8],"technology":[9],"for":[10,97,116],"next-generation":[11],"communication,":[12],"enabling":[13],"the":[14,69,136],"construction":[15,31],"of":[16],"high-fidelity":[17],"mappings":[18],"between":[19],"spatial":[20],"environments":[21],"and":[22,54],"channel":[23],"parameters":[24],"via":[25],"electromagnetic":[26],"information":[27],"analysis.":[28],"Traditional":[29],"CKM":[30,48],"methods":[32],"like":[33],"ray":[34],"tracing":[35],"are":[36],"computationally":[37],"intensive.":[38],"Recent":[39],"studies":[40],"utilizing":[41],"neural":[42],"networks":[43],"(NNs)":[44],"have":[45],"achieved":[46],"efficient":[47],"generation":[49],"with":[50,120],"reduced":[51],"computational":[52],"complexity":[53],"real-time":[55],"processing":[56],"capabilities.":[57],"Nevertheless,":[58],"existing":[59],"research":[60],"predominantly":[61],"focuses":[62],"on":[63],"single-antenna":[64],"systems,":[65],"failing":[66],"to":[67,73,124,153],"address":[68],"beamforming":[70],"requirements":[71],"inherent":[72],"MIMO":[74,83],"configurations.":[75],"Given":[76],"that":[77,135],"appropriate":[78],"precoding":[79,107],"vector":[80],"selection":[81],"in":[82,150],"systems":[84],"can":[85],"substantially":[86],"enhance":[87],"user":[88],"communication":[89],"rates,":[90],"this":[91],"paper":[92],"presents":[93],"TransUNet-based":[95],"framework":[96],"constructing":[98],"CKM,":[99],"which":[100],"effectively":[101],"incorporates":[102],"discrete":[103],"Fourier":[104],"transform":[105],"(DFT)":[106],"vectors.":[108,131],"The":[109,155],"proposed":[110,137],"architecture":[111],"combines":[112],"UNet":[114],"backbone":[115],"multiscale":[117],"feature":[118],"extraction":[119],"Transformer":[122],"module":[123],"capture":[125],"global":[126],"dependencies":[127],"among":[128],"encoded":[129],"linear":[130],"Experimental":[132],"results":[133],"demonstrate":[134],"method":[138],"outperforms":[139],"state-of-the-art":[140],"(SOTA)":[141],"deep":[142],"learning":[143],"(DL)":[144],"approaches,":[145],"yielding":[146],"17%":[148],"improvement":[149],"RMSE":[151],"compared":[152],"RadioWNet.":[154],"code":[156],"is":[157],"publicly":[158],"accessible":[159],"at":[160],"https://github.com/github-whh/TransUNet.":[161]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-20T00:00:00"}