{"id":"https://openalex.org/W4414539923","doi":"https://doi.org/10.1109/icc52391.2025.11161932","title":"Federated Reinforcement Learning-Based Resource Allocation in O-RAN Slicing for Metaverse","display_name":"Federated Reinforcement Learning-Based Resource Allocation in O-RAN Slicing for Metaverse","publication_year":2025,"publication_date":"2025-06-08","ids":{"openalex":"https://openalex.org/W4414539923","doi":"https://doi.org/10.1109/icc52391.2025.11161932"},"language":"en","primary_location":{"id":"doi:10.1109/icc52391.2025.11161932","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc52391.2025.11161932","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2025 - IEEE International Conference on Communications","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/A5013294154","display_name":"Ratna Mudi","orcid":"https://orcid.org/0000-0001-8993-7251"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Ratna Mudi","raw_affiliation_strings":["Université du Québec à Montréal,Department of Computer Science,Montreal,QC,Canada"],"affiliations":[{"raw_affiliation_string":"Université du Québec à Montréal,Department of Computer Science,Montreal,QC,Canada","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009168558","display_name":"Halima Elbiaze","orcid":"https://orcid.org/0000-0001-5681-6445"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Halima Elbiaze","raw_affiliation_strings":["Université du Québec à Montréal,Department of Computer Science,Montreal,QC,Canada"],"affiliations":[{"raw_affiliation_string":"Université du Québec à Montréal,Department of Computer Science,Montreal,QC,Canada","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5013294154"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.27738964,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"01","last_page":"07"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.8489000201225281,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.8489000201225281,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10273","display_name":"IoT and Edge/Fog Computing","score":0.7355999946594238,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.7110000252723694,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.7412999868392944},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.5006999969482422},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.4790000021457672},{"id":"https://openalex.org/keywords/quality-of-experience","display_name":"Quality of experience","score":0.4779999852180481},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.45809999108314514},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4336000084877014},{"id":"https://openalex.org/keywords/resource-allocation","display_name":"Resource allocation","score":0.4041000008583069},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.3971000015735626},{"id":"https://openalex.org/keywords/metaverse","display_name":"Metaverse","score":0.37770000100135803}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8503000140190125},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7412999868392944},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.5521000027656555},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.5006999969482422},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.4790000021457672},{"id":"https://openalex.org/C2779333187","wikidata":"https://www.wikidata.org/wiki/Q3132648","display_name":"Quality of experience","level":3,"score":0.4779999852180481},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.45809999108314514},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.4487000107765198},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4336000084877014},{"id":"https://openalex.org/C29202148","wikidata":"https://www.wikidata.org/wiki/Q287260","display_name":"Resource allocation","level":2,"score":0.4041000008583069},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.3971000015735626},{"id":"https://openalex.org/C53332860","wikidata":"https://www.wikidata.org/wiki/Q2632041","display_name":"Metaverse","level":3,"score":0.37770000100135803},{"id":"https://openalex.org/C108037233","wikidata":"https://www.wikidata.org/wiki/Q11375","display_name":"Wireless network","level":3,"score":0.3718999922275543},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.3443000018596649},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.3336000144481659},{"id":"https://openalex.org/C527821871","wikidata":"https://www.wikidata.org/wiki/Q228502","display_name":"Access control","level":2,"score":0.32899999618530273},{"id":"https://openalex.org/C2780609101","wikidata":"https://www.wikidata.org/wiki/Q17156588","display_name":"Resource management (computing)","level":2,"score":0.32269999384880066},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.313400000333786},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.30880001187324524},{"id":"https://openalex.org/C2984118289","wikidata":"https://www.wikidata.org/wiki/Q29954","display_name":"Power consumption","level":3,"score":0.3034000098705292},{"id":"https://openalex.org/C5119721","wikidata":"https://www.wikidata.org/wiki/Q220501","display_name":"Quality of service","level":2,"score":0.30160000920295715},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.2957000136375427},{"id":"https://openalex.org/C56685638","wikidata":"https://www.wikidata.org/wiki/Q2300474","display_name":"Power control","level":3,"score":0.29499998688697815},{"id":"https://openalex.org/C2776190703","wikidata":"https://www.wikidata.org/wiki/Q488148","display_name":"Slicing","level":2,"score":0.2721000015735626},{"id":"https://openalex.org/C93996380","wikidata":"https://www.wikidata.org/wiki/Q44127","display_name":"Server","level":2,"score":0.27129998803138733},{"id":"https://openalex.org/C68649174","wikidata":"https://www.wikidata.org/wiki/Q1379116","display_name":"Base station","level":2,"score":0.26820001006126404},{"id":"https://openalex.org/C200157131","wikidata":"https://www.wikidata.org/wiki/Q4854763","display_name":"Bandwidth allocation","level":3,"score":0.2574999928474426}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icc52391.2025.11161932","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc52391.2025.11161932","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2025 - IEEE International Conference on Communications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W3158459370","https://openalex.org/W3163231210","https://openalex.org/W4210482483","https://openalex.org/W4290997040","https://openalex.org/W4295832472","https://openalex.org/W4315629987","https://openalex.org/W4379382423","https://openalex.org/W4379659737","https://openalex.org/W4380365050","https://openalex.org/W4381946597","https://openalex.org/W4383960492","https://openalex.org/W4386558805","https://openalex.org/W4389544252","https://openalex.org/W4392729274","https://openalex.org/W4401609047","https://openalex.org/W4402809349"],"related_works":[],"abstract_inverted_index":{"Ensuring":[0],"high":[1,47],"Quality":[2],"of":[3],"Experience":[4],"(QoE)":[5],"is":[6,38],"crucial":[7],"for":[8,40,82,106,115],"seamless":[9],"wireless":[10],"access":[11,34],"in":[12,31],"immersive":[13],"metaverse":[14],"environments,":[15],"yet":[16],"this":[17,61],"goal":[18],"faces":[19],"challenges":[20],"due":[21],"to":[22,45,96,154],"constrained":[23],"communication":[24,92],"and":[25,91,93,100,129,150],"computing":[26],"resources.":[27],"Coordinating":[28],"x-applications":[29],"(xAPPs)":[30],"open":[32],"radio":[33],"network":[35,124],"(O-RAN)":[36],"effectively":[37],"essential":[39],"optimizing":[41],"these":[42],"limited":[43],"resources":[44],"meet":[46],"QoE":[48,75,119,149],"demands,":[49],"thus":[50],"enhancing":[51],"the":[52,83,116,118,144],"user":[53],"experience.":[54],"Federated":[55],"reinforcement":[56],"learning":[57],"(FRL)":[58],"further":[59],"supports":[60],"by":[62],"facilitating":[63],"collaboration":[64],"among":[65],"distributed":[66],"agents,":[67],"boosting":[68],"training":[69,138],"efficiency.":[70,139],"This":[71],"paper":[72],"proposes":[73],"a":[74,111],"utility":[76,120],"model":[77,121],"based":[78],"on":[79],"xAPPs":[80],"design":[81],"metaverse,":[84,117],"which":[85],"incorporates":[86],"energy":[87],"efficiency,":[88],"video":[89],"quality,":[90],"computation":[94],"delays":[95],"optimize":[97],"power":[98,127],"consumption":[99],"bandwidth":[101],"while":[102,136],"minimizing":[103],"delay.":[104],"Tailored":[105],"FRL-based":[107],"resource":[108,131],"allocation":[109],"within":[110],"sliced":[112],"O-RAN":[113],"architecture":[114],"manages":[122],"key":[123],"functions-such":[125],"as":[126],"control":[128],"physical":[130],"block":[132],"allocation-via":[133],"multi-agent":[134],"xAPPs,":[135],"improving":[137],"Numerical":[140],"results":[141],"demonstrate":[142],"that":[143],"proposed":[145],"algorithm":[146],"significantly":[147],"enhances":[148],"reduces":[151],"delay":[152],"compared":[153],"benchmark":[155],"algorithms.":[156]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-10T00:00:00"}