{"id":"https://openalex.org/W4406691611","doi":"https://doi.org/10.1002/nem.70000","title":"Music Transmission and Performance Optimization Based on the Integration of Artificial Intelligence and 6G Network Slice","display_name":"Music Transmission and Performance Optimization Based on the Integration of Artificial Intelligence and 6G Network Slice","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4406691611","doi":"https://doi.org/10.1002/nem.70000"},"language":"en","primary_location":{"id":"doi:10.1002/nem.70000","is_oa":false,"landing_page_url":"https://doi.org/10.1002/nem.70000","pdf_url":null,"source":{"id":"https://openalex.org/S204585504","display_name":"International Journal of Network Management","issn_l":"1055-7148","issn":["1055-7148","1099-1190"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Network Management","raw_type":"journal-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/A5100908321","display_name":"Honghui Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210146584","display_name":"Henan Forestry Vocational College","ror":"https://ror.org/050g87e49","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210146584"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Honghui Zhu","raw_affiliation_strings":["College of Early Childhood Education and Arts Henan Logistics Vocational College  Zhengzhou Henan China"],"raw_orcid":"https://orcid.org/0009-0006-6876-7293","affiliations":[{"raw_affiliation_string":"College of Early Childhood Education and Arts Henan Logistics Vocational College  Zhengzhou Henan China","institution_ids":["https://openalex.org/I4210146584"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5100908321"],"corresponding_institution_ids":["https://openalex.org/I4210146584"],"apc_list":{"value":3140,"currency":"USD","value_usd":3140},"apc_paid":null,"fwci":8.163,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.96388102,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"35","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14254","display_name":"Digital Media and Visual Art","score":0.9607999920845032,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/T14254","display_name":"Digital Media and Visual Art","score":0.9607999920845032,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/T12260","display_name":"Educational Technology and Pedagogy","score":0.958299994468689,"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/T13647","display_name":"AI and Big Data Applications","score":0.9157999753952026,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.9014151096343994},{"id":"https://openalex.org/keywords/transmission","display_name":"Transmission (telecommunications)","score":0.5795918703079224},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.510289192199707},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3468629717826843},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.259141743183136}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.9014151096343994},{"id":"https://openalex.org/C761482","wikidata":"https://www.wikidata.org/wiki/Q118093","display_name":"Transmission (telecommunications)","level":2,"score":0.5795918703079224},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.510289192199707},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3468629717826843},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.259141743183136}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1002/nem.70000","is_oa":false,"landing_page_url":"https://doi.org/10.1002/nem.70000","pdf_url":null,"source":{"id":"https://openalex.org/S204585504","display_name":"International Journal of Network Management","issn_l":"1055-7148","issn":["1055-7148","1099-1190"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Network Management","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W2945035284","https://openalex.org/W3013018332","https://openalex.org/W3165559782","https://openalex.org/W4375956147","https://openalex.org/W4384340606","https://openalex.org/W4386231202","https://openalex.org/W4387869966","https://openalex.org/W4387870282","https://openalex.org/W4387872682","https://openalex.org/W4389296300","https://openalex.org/W4389317821","https://openalex.org/W4389712590","https://openalex.org/W4391359033","https://openalex.org/W4393864584","https://openalex.org/W4397022574","https://openalex.org/W4399151177","https://openalex.org/W4399351151","https://openalex.org/W4400661474","https://openalex.org/W4401507345","https://openalex.org/W4401683126","https://openalex.org/W4403284806","https://openalex.org/W4403937529","https://openalex.org/W6981503853"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W3046775127","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474"],"abstract_inverted_index":{"ABSTRACT":[0],"Network":[1],"slicing,":[2],"which":[3],"enables":[4],"efficient":[5],"resource":[6,46,92,209,219],"management":[7,47],"to":[8,76,171,216,239],"meet":[9],"specific":[10],"service":[11,101,148],"requirements,":[12],"provides":[13],"a":[14,161,182,197,254,265],"scalable":[15],"solution":[16],"for":[17,85,151,188,207],"optimizing":[18,36],"music":[19,42,53,74,87,153,173,274],"transmission":[20],"and":[21,29,51,73,82,99,143,175,191,228,264,275,292],"live":[22,37,152,273],"performance":[23,49,174,241],"in":[24,55,118,272,286],"mobile":[25,277],"networks":[26],"beyond":[27],"5G":[28],"into":[30],"6G.":[31],"The":[32,211],"research":[33],"focuses":[34],"on":[35,231],"performances":[38],"as":[39,41,70],"well":[40,124],"transmission.":[43,176],"Since":[44],"AI\u2010driven":[45],"improves":[48],"quality":[50,83,146,261],"real\u2010time":[52,86,208],"streaming":[54],"dynamic":[56],"6G":[57,156],"network":[58,103,116,121,132,186,194,214,234,297],"situations,":[59],"these":[60],"factors":[61],"are":[62,105],"interconnected.":[63],"This":[64],"approach":[65,249],"allows":[66],"multiple":[67],"tenants,":[68],"such":[69],"event":[71],"organizers":[72],"producers,":[75],"share":[77],"infrastructure":[78,110],"while":[79],"customizing":[80],"communication":[81],"standards":[84],"services.":[88],"To":[89],"ensure":[90],"optimal":[91],"allocation,":[93,220],"including":[94],"high":[95],"bandwidth,":[96],"low":[97],"latency,":[98,288],"consistent":[100],"quality,":[102,291],"slices":[104],"dynamically":[106,225],"configured":[107],"by":[108,167,202],"the":[109,113,119,129,138,144,158,247,282],"provider.":[111],"Although":[112],"implementation":[114],"of":[115,140,147,193,256,262,268],"slicing":[117,164],"core":[120],"has":[122],"been":[123],"studied,":[125],"applying":[126],"it":[127],"within":[128],"radio":[130],"access":[131],"(RAN)":[133],"presents":[134],"challenges,":[135],"especially":[136],"given":[137],"unpredictability":[139],"wireless":[141],"channels":[142],"strict":[145],"(QoS)":[149],"demands":[150],"streaming.":[154],"For":[155],"networks,":[157],"article":[159],"suggests":[160],"tenant\u2010driven":[162],"RAN":[163],"method":[165],"improved":[166],"artificial":[168],"intelligence":[169],"(AI)":[170],"maximize":[172],"A":[177],"hybrid":[178],"AI":[179],"framework":[180],"integrates":[181],"deep":[183,198],"recurrent":[184],"neural":[185],"(DRNN)":[187],"continuous":[189],"monitoring":[190],"prediction":[192],"conditions":[195],"with":[196,223],"Q\u2010network":[199],"(DQN)":[200],"augmented":[201],"prioritized":[203],"experience":[204],"replay":[205],"(PER)":[206],"adaptation.":[210],"DRNN":[212],"forecasts":[213],"states":[215],"guide":[217],"high\u2010level":[218],"whereas":[221],"DQN":[222],"PER":[224],"manages":[226],"routing":[227],"bandwidth":[229,266],"based":[230],"past":[232],"critical":[233],"states,":[235],"enabling":[236],"rapid":[237],"responses":[238],"fluctuating":[240],"demands.":[242],"Comparative":[243],"results":[244,271],"indicate":[245],"that":[246],"suggested":[248],"outperforms":[250],"conventional":[251],"techniques,":[252],"achieving":[253],"latency":[255],"25":[257],"ms,":[258],"an":[259],"audio":[260,290],"4.6,":[263],"utilization":[267],"90%.":[269],"Simulation":[270],"enhanced":[276],"broadband":[278],"(eMBB)":[279],"environments":[280],"demonstrate":[281],"proposed":[283],"approach's":[284],"effectiveness":[285],"minimizing":[287],"enhancing":[289],"stabilizing":[293],"transmission,":[294],"surpassing":[295],"traditional":[296],"allocation":[298],"techniques.":[299]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}