{"id":"https://openalex.org/W4414942786","doi":"https://doi.org/10.1109/lwc.2026.3668310","title":"Meta-Reinforcement Learning for Fast and Data-Efficient Spectrum Allocation in Dynamic Wireless Networks","display_name":"Meta-Reinforcement Learning for Fast and Data-Efficient Spectrum Allocation in Dynamic Wireless Networks","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W4414942786","doi":"https://doi.org/10.1109/lwc.2026.3668310"},"language":"en","primary_location":{"id":"doi:10.1109/lwc.2026.3668310","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lwc.2026.3668310","pdf_url":null,"source":{"id":"https://openalex.org/S2500830676","display_name":"IEEE Wireless Communications Letters","issn_l":"2162-2337","issn":["2162-2337","2162-2345"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Wireless Communications Letters","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2507.10619","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114353162","display_name":"Oluwaseyi Giwa","orcid":null},"institutions":[{"id":"https://openalex.org/I148561064","display_name":"African Institute for Mathematical Sciences","ror":"https://ror.org/02f9k5d27","country_code":"ZA","type":"education","lineage":["https://openalex.org/I148561064"]}],"countries":["ZA"],"is_corresponding":false,"raw_author_name":"Oluwaseyi Giwa","raw_affiliation_strings":["African Institute for Mathematical Sciences, Muizenberg, South Africa"],"raw_orcid":"https://orcid.org/0009-0001-5771-7446","affiliations":[{"raw_affiliation_string":"African Institute for Mathematical Sciences, Muizenberg, South Africa","institution_ids":["https://openalex.org/I148561064"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Tobi Ebenezer Awodumila","orcid":"https://orcid.org/0009-0001-5637-5827"},"institutions":[{"id":"https://openalex.org/I148561064","display_name":"African Institute for Mathematical Sciences","ror":"https://ror.org/02f9k5d27","country_code":"ZA","type":"education","lineage":["https://openalex.org/I148561064"]}],"countries":["ZA"],"is_corresponding":false,"raw_author_name":"Tobi Ebenezer Awodumila","raw_affiliation_strings":["African Institute for Mathematical Sciences, Muizenberg, South Africa"],"raw_orcid":"https://orcid.org/0009-0001-5637-5827","affiliations":[{"raw_affiliation_string":"African Institute for Mathematical Sciences, Muizenberg, South Africa","institution_ids":["https://openalex.org/I148561064"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Muhammad Ahmed Mohsin","orcid":"https://orcid.org/0009-0005-2766-0345"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Muhammad Ahmed Mohsin","raw_affiliation_strings":["Stanford University, Stanford, CA, USA"],"raw_orcid":"https://orcid.org/0009-0005-2766-0345","affiliations":[{"raw_affiliation_string":"Stanford University, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032205160","display_name":"Ahsan Bilal","orcid":null},"institutions":[{"id":"https://openalex.org/I8692664","display_name":"University of Oklahoma","ror":"https://ror.org/02aqsxs83","country_code":"US","type":"education","lineage":["https://openalex.org/I8692664"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ahsan Bilal","raw_affiliation_strings":["School of Computer Science, University of Oklahoma, Norman, OK, USA"],"raw_orcid":"https://orcid.org/0009-0002-7044-9316","affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Oklahoma, Norman, OK, USA","institution_ids":["https://openalex.org/I8692664"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057961688","display_name":"Muhammad Ali Jamshed","orcid":"https://orcid.org/0000-0002-2141-9025"},"institutions":[{"id":"https://openalex.org/I7882870","display_name":"University of Glasgow","ror":"https://ror.org/00vtgdb53","country_code":"GB","type":"education","lineage":["https://openalex.org/I7882870"]},{"id":"https://openalex.org/I867661903","display_name":"City of Glasgow College","ror":"https://ror.org/0403kv531","country_code":"GB","type":"education","lineage":["https://openalex.org/I867661903"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Muhammad Ali Jamshed","raw_affiliation_strings":["College of Science and Engineering, University of Glasgow, Glasgow, U.K"],"raw_orcid":"https://orcid.org/0000-0002-2141-9025","affiliations":[{"raw_affiliation_string":"College of Science and Engineering, University of Glasgow, Glasgow, U.K","institution_ids":["https://openalex.org/I7882870","https://openalex.org/I867661903"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":7.2752,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.93325551,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"15","issue":null,"first_page":"2000","last_page":"2004"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10579","display_name":"Cognitive Radio Networks and Spectrum Sensing","score":0.9891999959945679,"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"}},"topics":[{"id":"https://openalex.org/T10579","display_name":"Cognitive Radio Networks and Spectrum Sensing","score":0.9891999959945679,"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/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.9779999852180481,"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/T11158","display_name":"Wireless Networks and Protocols","score":0.963699996471405,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.7092999815940857},{"id":"https://openalex.org/keywords/wireless-network","display_name":"Wireless network","score":0.5748999714851379},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.5620999932289124},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5425000190734863},{"id":"https://openalex.org/keywords/backhaul","display_name":"Backhaul (telecommunications)","score":0.4823000133037567},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.4821000099182129},{"id":"https://openalex.org/keywords/frequency-allocation","display_name":"Frequency allocation","score":0.4790000021457672},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.4162999987602234},{"id":"https://openalex.org/keywords/spectrum-management","display_name":"Spectrum management","score":0.4083000123500824},{"id":"https://openalex.org/keywords/wireless-sensor-network","display_name":"Wireless sensor network","score":0.37720000743865967}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8529000282287598},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7092999815940857},{"id":"https://openalex.org/C108037233","wikidata":"https://www.wikidata.org/wiki/Q11375","display_name":"Wireless network","level":3,"score":0.5748999714851379},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.5644999742507935},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.5620999932289124},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5425000190734863},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.5026000142097473},{"id":"https://openalex.org/C103760667","wikidata":"https://www.wikidata.org/wiki/Q798444","display_name":"Backhaul (telecommunications)","level":3,"score":0.4823000133037567},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.4821000099182129},{"id":"https://openalex.org/C134579502","wikidata":"https://www.wikidata.org/wiki/Q1455619","display_name":"Frequency allocation","level":2,"score":0.4790000021457672},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.4162999987602234},{"id":"https://openalex.org/C63029442","wikidata":"https://www.wikidata.org/wiki/Q6504978","display_name":"Spectrum management","level":4,"score":0.4083000123500824},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.37720000743865967},{"id":"https://openalex.org/C2780609101","wikidata":"https://www.wikidata.org/wiki/Q17156588","display_name":"Resource management (computing)","level":2,"score":0.3610999882221222},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.3596999943256378},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3425000011920929},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.3402000069618225},{"id":"https://openalex.org/C182448111","wikidata":"https://www.wikidata.org/wiki/Q7281197","display_name":"Radio resource management","level":4,"score":0.33820000290870667},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.33329999446868896},{"id":"https://openalex.org/C200157131","wikidata":"https://www.wikidata.org/wiki/Q4854763","display_name":"Bandwidth allocation","level":3,"score":0.3255000114440918},{"id":"https://openalex.org/C153646914","wikidata":"https://www.wikidata.org/wiki/Q535695","display_name":"Cellular network","level":2,"score":0.31859999895095825},{"id":"https://openalex.org/C29202148","wikidata":"https://www.wikidata.org/wiki/Q287260","display_name":"Resource allocation","level":2,"score":0.31470000743865967},{"id":"https://openalex.org/C188116033","wikidata":"https://www.wikidata.org/wiki/Q2664563","display_name":"Q-learning","level":3,"score":0.2964000105857849},{"id":"https://openalex.org/C2778445095","wikidata":"https://www.wikidata.org/wiki/Q18354077","display_name":"Sample complexity","level":2,"score":0.2921000123023987},{"id":"https://openalex.org/C114237682","wikidata":"https://www.wikidata.org/wiki/Q5072483","display_name":"Channel allocation schemes","level":3,"score":0.29170000553131104},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.27639999985694885},{"id":"https://openalex.org/C46637626","wikidata":"https://www.wikidata.org/wiki/Q6693015","display_name":"Low latency (capital markets)","level":2,"score":0.2728999853134155},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.2687999904155731},{"id":"https://openalex.org/C149946192","wikidata":"https://www.wikidata.org/wiki/Q3235733","display_name":"Cognitive radio","level":3,"score":0.2653999924659729},{"id":"https://openalex.org/C137246740","wikidata":"https://www.wikidata.org/wiki/Q583970","display_name":"Spectral efficiency","level":3,"score":0.2615000009536743},{"id":"https://openalex.org/C41971633","wikidata":"https://www.wikidata.org/wiki/Q6398155","display_name":"Key distribution in wireless sensor networks","level":4,"score":0.26019999384880066},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.2549999952316284}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/lwc.2026.3668310","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lwc.2026.3668310","pdf_url":null,"source":{"id":"https://openalex.org/S2500830676","display_name":"IEEE Wireless Communications Letters","issn_l":"2162-2337","issn":["2162-2337","2162-2345"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Wireless Communications Letters","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2507.10619","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2507.10619","pdf_url":"https://arxiv.org/pdf/2507.10619","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},{"id":"doi:10.48550/arxiv.2507.10619","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2507.10619","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2507.10619","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2507.10619","pdf_url":"https://arxiv.org/pdf/2507.10619","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Efficient":[0],"spectrum":[1,135],"allocation":[2],"is":[3],"vital":[4],"for":[5,137],"5G/6G":[6],"networks,":[7],"yet":[8],"traditional":[9],"deep":[10],"reinforcement":[11],"learning":[12],"(DRL)":[13],"methods":[14],"suffer":[15],"from":[16],"high":[17],"sample":[18],"complexity":[19],"and":[20,46,67,79,104,113,133],"unsafe":[21],"exploration":[22],"that":[23,37,128],"can":[24],"disrupt":[25],"network":[26,65],"stability.":[27],"To":[28],"address":[29],"these":[30],"challenges,":[31],"we":[32],"propose":[33],"a":[34,39,70,76,84,95],"meta-learning":[35,56,61,129],"framework":[36],"learns":[38],"robust":[40],"initial":[41],"policy":[42],"capable":[43],"of":[44,98,116,120],"rapid":[45],"safe":[47],"adaptation":[48],"to":[49,111],"changing":[50],"wireless":[51,139],"conditions.":[52],"We":[53],"implement":[54],"three":[55],"architectures":[57],"using":[58],"model-agnostic":[59],"techniques\u2014model-agnostic":[60],"(MAML),":[62],"recurrent":[63],"neural":[64],"(RNN),":[66],"RNN":[68],"with":[69],"self-attention":[71],"mechanism\u2014and":[72],"compare":[73],"them":[74],"against":[75],"DRL":[77],"baseline":[78],"classical":[80],"heuristic":[81],"approaches":[82],"in":[83],"dynamic":[85],"integrated":[86],"access/":[87],"backhaul":[88],"(IAB)":[89],"environment.":[90],"The":[91],"attention-based":[92],"agent":[93],"achieves":[94],"peak":[96],"throughput":[97],"\u2248":[99],"49":[100],"Mbps,":[101],"reducing":[102],"SINR":[103],"latency":[105],"violations":[106],"by":[107],"over":[108],"60%":[109],"relative":[110],"PPO,":[112],"attains":[114],"97%":[115],"the":[117,121],"fairness":[118],"level":[119],"exhaustive-search":[122],"upper":[123],"bound.":[124],"These":[125],"results":[126],"demonstrate":[127],"enables":[130],"data-efficient,":[131],"reliable,":[132],"scalable":[134],"management":[136],"next-generation":[138],"systems.":[140]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-08-16T07:02:28.622633","created_date":"2025-10-08T00:00:00"}
