{"id":"https://openalex.org/W4413925714","doi":"https://doi.org/10.1109/access.2025.3605249","title":"Data-Driven Learning of Two-Stage Beamformers in Passive IRS-Assisted Systems With Inexact Oracles","display_name":"Data-Driven Learning of Two-Stage Beamformers in Passive IRS-Assisted Systems With Inexact Oracles","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4413925714","doi":"https://doi.org/10.1109/access.2025.3605249"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3605249","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3605249","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3605249","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017796051","display_name":"Spyridon Pougkakiotis","orcid":"https://orcid.org/0000-0001-7903-9335"},"institutions":[{"id":"https://openalex.org/I183935753","display_name":"King's College London","ror":"https://ror.org/0220mzb33","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I183935753"]},{"id":"https://openalex.org/I4210119896","display_name":"King's College School","ror":"https://ror.org/02bbqcn27","country_code":"GB","type":"education","lineage":["https://openalex.org/I4210119896"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Spyridon Pougkakiotis","raw_affiliation_strings":["Department of Mathematics, King&#x2019;s College London, London, U.K","Department of Mathematics, King&#x2019;s College London, London, UK"],"raw_orcid":"https://orcid.org/0000-0001-7903-9335","affiliations":[{"raw_affiliation_string":"Department of Mathematics, King&#x2019;s College London, London, U.K","institution_ids":["https://openalex.org/I183935753","https://openalex.org/I4210119896"]},{"raw_affiliation_string":"Department of Mathematics, King&#x2019;s College London, London, UK","institution_ids":["https://openalex.org/I183935753","https://openalex.org/I4210119896"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005929408","display_name":"H. N. Hashmi","orcid":"https://orcid.org/0000-0002-3008-3535"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hassaan Hashmi","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Yale University, New Haven, CT, USA"],"raw_orcid":"https://orcid.org/0000-0002-3008-3535","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Yale University, New Haven, CT, USA","institution_ids":["https://openalex.org/I32971472"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091493591","display_name":"Dionysios S. Kalogerias","orcid":"https://orcid.org/0000-0002-3459-5044"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dionysis Kalogerias","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Yale University, New Haven, CT, USA"],"raw_orcid":"https://orcid.org/0000-0002-3459-5044","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Yale University, New Haven, CT, USA","institution_ids":["https://openalex.org/I32971472"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08731785,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":null,"first_page":"154984","last_page":"155002"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9717000126838684,"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/T10320","display_name":"Neural Networks and Applications","score":0.9717000126838684,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9366999864578247,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12564","display_name":"Sensor Technology and Measurement Systems","score":0.9179999828338623,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7282574772834778},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41065219044685364}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7282574772834778},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41065219044685364}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/access.2025.3605249","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3605249","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:kclpure.kcl.ac.uk:publications/0b1f1097-19ae-47a7-a043-93b75049cdfd","is_oa":true,"landing_page_url":"https://kclpure.kcl.ac.uk/portal/en/publications/0b1f1097-19ae-47a7-a043-93b75049cdfd","pdf_url":null,"source":{"id":"https://openalex.org/S4306400216","display_name":"Research Portal (King's College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I183935753","host_organization_name":"King's College London","host_organization_lineage":["https://openalex.org/I183935753"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Pougkakiotis, S, Hashmi, H & Kalogerias, D 2025, 'Data-Driven Learning of Two-Stage Beamformers in Passive IRS-Assisted Systems with Inexact Oracles', IEEE Access, vol. 13, pp. 154984-155002. https://doi.org/10.1109/ACCESS.2025.3605249","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:doaj.org/article:513ad99ae72445279816efdca29cdd4f","is_oa":true,"landing_page_url":"https://doaj.org/article/513ad99ae72445279816efdca29cdd4f","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 13, Pp 154984-155002 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3605249","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3605249","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3830358332","display_name":"CIF: Small: Risk-Aware Resource Allocation for Robust Wireless Autonomy","funder_award_id":"2242215","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G497264525","display_name":null,"funder_award_id":"FA8650-20-2-5506","funder_id":"https://openalex.org/F4320338294","funder_display_name":"Air Force Research Laboratory"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320338294","display_name":"Air Force Research Laboratory","ror":"https://ror.org/02e2egq70"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":66,"referenced_works":["https://openalex.org/W1970830346","https://openalex.org/W2005895359","https://openalex.org/W2021361347","https://openalex.org/W2054692642","https://openalex.org/W2093488901","https://openalex.org/W2141682101","https://openalex.org/W2144000019","https://openalex.org/W2149479912","https://openalex.org/W2152463001","https://openalex.org/W2161696874","https://openalex.org/W2294586855","https://openalex.org/W2331639718","https://openalex.org/W2398409936","https://openalex.org/W2546737567","https://openalex.org/W2605344455","https://openalex.org/W2784709112","https://openalex.org/W2883094398","https://openalex.org/W2893303065","https://openalex.org/W2899403756","https://openalex.org/W2955133642","https://openalex.org/W2962942052","https://openalex.org/W2963190258","https://openalex.org/W2969424089","https://openalex.org/W2970297297","https://openalex.org/W2990747873","https://openalex.org/W2996611387","https://openalex.org/W3005476696","https://openalex.org/W3034281970","https://openalex.org/W3038534820","https://openalex.org/W3109685033","https://openalex.org/W3116920802","https://openalex.org/W3120117232","https://openalex.org/W3133971993","https://openalex.org/W3134059753","https://openalex.org/W3154292415","https://openalex.org/W3160036209","https://openalex.org/W3175883525","https://openalex.org/W3185482389","https://openalex.org/W3197545540","https://openalex.org/W4283029880","https://openalex.org/W4285291292","https://openalex.org/W4286569445","https://openalex.org/W4296915796","https://openalex.org/W4312805416","https://openalex.org/W4313069424","https://openalex.org/W4320015838","https://openalex.org/W4327661444","https://openalex.org/W4360897659","https://openalex.org/W4372259820","https://openalex.org/W4376481228","https://openalex.org/W4377231442","https://openalex.org/W4384303901","https://openalex.org/W4385694541","https://openalex.org/W4386523619","https://openalex.org/W4387623793","https://openalex.org/W4387667441","https://openalex.org/W4387913972","https://openalex.org/W4389331899","https://openalex.org/W4390204105","https://openalex.org/W4390905806","https://openalex.org/W4391492622","https://openalex.org/W4391582659","https://openalex.org/W4392824812","https://openalex.org/W4395471122","https://openalex.org/W4404914322","https://openalex.org/W4407168515"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"The":[0],"purpose":[1],"of":[2,8,43,109,142,160,185,200,212,251,265],"this":[3,34],"work":[4],"is":[5,129,136,177],"the":[6,41,73,110,120,175,183,242,249,263],"development":[7],"an":[9,131],"efficient":[10,258],"data-driven":[11],"and":[12,66,95,98,163,245,259],"model-free":[13],"unsupervised":[14],"learning":[15],"framework":[16],"for":[17,56,262],"achieving":[18],"fully":[19],"passive":[20],"intelligent":[21],"reflective":[22],"surface":[23],"(IRS)-assisted":[24],"optimal":[25,144,270],"joint":[26],"short/long-term":[27],"beamforming":[28,124,145,271],"in":[29,72,117,209,233],"wireless":[30],"communication":[31],"networks.":[32],"Under":[33],"challenging":[35,187],"setting,":[36],"our":[37,180],"contribution":[38],"amounts":[39],"to":[40,105,151,205,215],"design":[42],"novelIRS":[44],"training":[45],"schemes\u2014termediZoSGAherein\u2014":[46],"relying":[47],"on":[48,138,248],"a":[49,139,210,216],"zeroth-order":[50],"stochastic":[51,60],"gradient":[52],"ascent":[53],"methodology,":[54],"suitable":[55],"tackling":[57],"nonconvex":[58,188],"twostage":[59],"optimization":[61],"problems":[62],"with":[63,193],"continuous":[64],"uncertainty":[65],"unknown":[67],"(or":[68],"\u2018\u2018black-box\u2019\u2019)":[69],"terms":[70],"present":[71],"corresponding":[74],"objective":[75],"function,":[76],"via":[77],"utilization":[78],"ofinexact":[79],"short-term":[80],"evaluation":[81],"oracles.":[82],"Our":[83],"findings":[84],"are":[85,202],"as":[86],"follows:We":[87],"showcase":[88],"that":[89],"iZoSGA":[90,135,201],"can":[91,255],"operate":[92,152],"under":[93,273],"realistic":[94,274],"general":[96,266],"assumptions,":[97],"establish":[99],"its":[100,246],"(non-asymptotic)":[101],"convergence":[102],"rate":[103],"close":[104],"some":[106],"stationary":[107],"point":[108],"associated":[111,192],"two-stage":[112],"(i.e.,":[113,122],"short/long-term)":[114],"problem,":[115],"particularly":[116,207],"cases":[118],"where":[119],"second-stage":[121],"short-term)":[123],"problem":[125],"(e.g.,":[126,227],"transmit":[127],"precoding)":[128],"solvedinexactlyusing":[130],"arbitrary":[132,165],"(inexact)":[133],"algorithm.":[134],"applicable":[137],"wide":[140],"variety":[141],"IRS-assisted":[143,269],"settings,":[146],"while":[147],"also":[148],"being":[149],"able":[150],"without":[153],"(cascaded)":[154],"channel":[155,161],"model":[156],"assumptions":[157],"or":[158],"knowledge":[159],"statistics,":[162],"over":[164],"IRS":[166,194,225],"physical":[167,224],"configurations;":[168],"thus,":[169],"no":[170],"active":[171],"sensing":[172],"capability":[173],"at":[174],"IRS(s)":[176],"needed.":[178],"Additionally,":[179],"approach":[181],"bypasses":[182],"need":[184],"imposing":[186],"unit-modulus":[189],"constraints,":[190],"typically":[191],"parameter":[195],"optimization.":[196],"Several":[197],"algorithmic":[198],"variants":[199],"numerically":[203],"demonstrated":[204],"be":[206],"effective":[208],"range":[211],"experiments":[213],"pertaining":[214],"well-studied":[217],"MISO":[218],"downlink":[219],"model,":[220],"including":[221],"scenarios":[222],"demanding":[223],"tuning":[226],"directly":[228],"through":[229],"varactor":[230],"capacitances),":[231],"even":[232],"large-scale":[234],"regimes.":[235],"Overall":[236],"we":[237,254],"demonstrate":[238],"that,":[239],"by":[240],"leveraging":[241],"developed":[243],"theory":[244],"insights":[247],"propagation":[250],"oracle":[252],"errors,":[253],"create":[256],"highly":[257],"scalable":[260],"algorithms":[261],"solution":[264],"(possibly":[267],"large-scale)":[268],"problems,":[272],"assumptions.":[275]},"counts_by_year":[],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}
