{"id":"https://openalex.org/W4317418718","doi":"https://doi.org/10.1109/vtc2022-fall57202.2022.10013032","title":"STARS Enabled Integrated Sensing and Communications: A CRB optimization Perspective","display_name":"STARS Enabled Integrated Sensing and Communications: A CRB optimization Perspective","publication_year":2022,"publication_date":"2022-09-01","ids":{"openalex":"https://openalex.org/W4317418718","doi":"https://doi.org/10.1109/vtc2022-fall57202.2022.10013032"},"language":"en","primary_location":{"id":"doi:10.1109/vtc2022-fall57202.2022.10013032","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtc2022-fall57202.2022.10013032","pdf_url":null,"source":{"id":"https://openalex.org/S4363607792","display_name":"2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)","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/A5101635009","display_name":"Zhaolin Wang","orcid":"https://orcid.org/0000-0003-4614-0175"},"institutions":[{"id":"https://openalex.org/I166337079","display_name":"Queen Mary University of London","ror":"https://ror.org/026zzn846","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I166337079"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Zhaolin Wang","raw_affiliation_strings":["Queen Mary University of London,London,UK","Queen Mary University of London, London, UK"],"affiliations":[{"raw_affiliation_string":"Queen Mary University of London,London,UK","institution_ids":["https://openalex.org/I166337079"]},{"raw_affiliation_string":"Queen Mary University of London, London, UK","institution_ids":["https://openalex.org/I166337079"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056349361","display_name":"Xidong Mu","orcid":"https://orcid.org/0000-0001-8351-360X"},"institutions":[{"id":"https://openalex.org/I166337079","display_name":"Queen Mary University of London","ror":"https://ror.org/026zzn846","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I166337079"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Xidong Mu","raw_affiliation_strings":["Queen Mary University of London,London,UK","Queen Mary University of London, London, UK"],"affiliations":[{"raw_affiliation_string":"Queen Mary University of London,London,UK","institution_ids":["https://openalex.org/I166337079"]},{"raw_affiliation_string":"Queen Mary University of London, London, UK","institution_ids":["https://openalex.org/I166337079"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076863392","display_name":"Yuanwei Liu","orcid":"https://orcid.org/0000-0002-6389-8941"},"institutions":[{"id":"https://openalex.org/I166337079","display_name":"Queen Mary University of London","ror":"https://ror.org/026zzn846","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I166337079"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yuanwei Liu","raw_affiliation_strings":["Queen Mary University of London,London,UK","Queen Mary University of London, London, UK"],"affiliations":[{"raw_affiliation_string":"Queen Mary University of London,London,UK","institution_ids":["https://openalex.org/I166337079"]},{"raw_affiliation_string":"Queen Mary University of London, London, UK","institution_ids":["https://openalex.org/I166337079"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101635009"],"corresponding_institution_ids":["https://openalex.org/I166337079"],"apc_list":null,"apc_paid":null,"fwci":2.5794,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.92005633,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":98},"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/T11458","display_name":"Advanced Wireless Communication Technologies","score":0.9995999932289124,"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/T11458","display_name":"Advanced Wireless Communication Technologies","score":0.9995999932289124,"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9930999875068665,"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/T10891","display_name":"Radar Systems and Signal Processing","score":0.9884999990463257,"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/stars","display_name":"Stars","score":0.7366765141487122},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6866933107376099},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.5377272963523865},{"id":"https://openalex.org/keywords/clutter","display_name":"Clutter","score":0.46936729550361633},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.43446481227874756},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3412310481071472},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.23525094985961914},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21022316813468933},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.19216910004615784},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.08635321259498596}],"concepts":[{"id":"https://openalex.org/C150846664","wikidata":"https://www.wikidata.org/wiki/Q7602306","display_name":"Stars","level":2,"score":0.7366765141487122},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6866933107376099},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.5377272963523865},{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.46936729550361633},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.43446481227874756},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3412310481071472},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.23525094985961914},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21022316813468933},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.19216910004615784},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.08635321259498596},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/vtc2022-fall57202.2022.10013032","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtc2022-fall57202.2022.10013032","pdf_url":null,"source":{"id":"https://openalex.org/S4363607792","display_name":"2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)","raw_type":"proceedings-article"},{"id":"pmh:oai:hub.hku.hk:10722/349856","is_oa":false,"landing_page_url":"https://hub.hku.hk/handle/10722/349856","pdf_url":null,"source":{"id":"https://openalex.org/S4377196271","display_name":"The HKU Scholars Hub (University of Hong Kong)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I889458895","host_organization_name":"University of Hong Kong","host_organization_lineage":["https://openalex.org/I889458895"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference_Paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W250076511","https://openalex.org/W1542938076","https://openalex.org/W1996215314","https://openalex.org/W2171576754","https://openalex.org/W3036056878","https://openalex.org/W3038047043","https://openalex.org/W3135998278","https://openalex.org/W3159402647","https://openalex.org/W3165173280","https://openalex.org/W3205217150","https://openalex.org/W3217184862","https://openalex.org/W4206542241","https://openalex.org/W4214867678","https://openalex.org/W4226165103","https://openalex.org/W4250589301","https://openalex.org/W4300770901"],"related_works":["https://openalex.org/W2130674020","https://openalex.org/W2093748878","https://openalex.org/W2333771223","https://openalex.org/W2120056845","https://openalex.org/W1981531423","https://openalex.org/W4394861761","https://openalex.org/W1977371217","https://openalex.org/W2035264131","https://openalex.org/W1679012645","https://openalex.org/W1925461966"],"abstract_inverted_index":{"A":[0,33,85],"simultaneously":[1],"transmitting":[2],"and":[3,11,29,53],"reflecting":[4],"intelligent":[5,143],"surface":[6],"(STARS)":[7],"enabled":[8],"integrated":[9],"sensing":[10,27,71,147],"communications":[12],"(ISAC)":[13],"framework":[14],"is":[15,21,45,73,76,88,129],"proposed,":[16],"where":[17,37],"the":[18,43,49,63,70,81,92,110,114,124,140,155],"whole":[19],"space":[20,28],"divided":[22],"by":[23,152],"STARS":[24,137,153],"into":[25,97],"a":[26,30,98],"communication":[31,83],"space.":[32],"novel":[34,86],"sensing-at-STARS":[35],"structure,":[36],"dedicated":[38],"sensors":[39],"are":[40],"installed":[41],"at":[42],"STARS,":[44],"proposed":[46,89],"to":[47,80,90,108],"address":[48,109],"significant":[50],"path":[51],"loss":[52],"clutter":[54],"interference":[55],"for":[56],"sensing.":[57],"The":[58,131],"Cram\u00e9r-Rao":[59],"bound":[60],"(CRB)":[61],"of":[62,69],"2-dimension":[64],"(2D)":[65],"direction-of-arrivals":[66],"(DOAs)":[67],"estimation":[68],"target":[72],"derived,":[74],"which":[75],"then":[77],"minimized":[78],"subject":[79],"minimum":[82],"requirement.":[84],"approach":[87],"transform":[91],"complicated":[93],"CRB":[94],"minimization":[95],"problem":[96],"trackable":[99],"modified":[100,115],"Fisher":[101],"information":[102],"matrix":[103],"(FIM)":[104],"optimization":[105],"problem.":[106],"Moreover,":[107],"coupled":[111],"issue":[112],"in":[113],"FIM,":[116],"an":[117],"efficient":[118],"double-loop":[119],"iterative":[120],"algorithm":[121],"based":[122],"on":[123],"penalty":[125],"dual":[126],"decomposition":[127],"method":[128],"conceived.":[130],"numerical":[132],"results":[133],"demonstrate":[134],"that:":[135],"1)":[136],"significantly":[138],"outperforms":[139],"conventional":[141],"transmitting/reflecting-only":[142],"surface;":[144],"2)":[145],"High":[146],"accuracy":[148],"can":[149],"be":[150],"achieved":[151],"using":[154],"practical":[156],"2D":[157],"maximum":[158],"likelihood":[159],"estimator.":[160]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
