{"id":"https://openalex.org/W4403762125","doi":"https://doi.org/10.48550/arxiv.2407.11747","title":"PandORA: Automated Design and Comprehensive Evaluation of Deep Reinforcement Learning Agents for Open RAN","display_name":"PandORA: Automated Design and Comprehensive Evaluation of Deep Reinforcement Learning Agents for Open RAN","publication_year":2024,"publication_date":"2024-05-23","ids":{"openalex":"https://openalex.org/W4403762125","doi":"https://doi.org/10.48550/arxiv.2407.11747"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2407.11747","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2407.11747","pdf_url":"https://arxiv.org/pdf/2407.11747","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2407.11747","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5063193816","display_name":"Maria Tsampazi","orcid":"https://orcid.org/0009-0007-4030-6281"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Tsampazi, Maria","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053788606","display_name":"Salvatore D\u2019Oro","orcid":"https://orcid.org/0000-0002-7690-0449"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"D'Oro, Salvatore","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007933623","display_name":"Michele Polese","orcid":"https://orcid.org/0000-0002-9740-134X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Polese, Michele","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005032046","display_name":"Leonardo Bonati","orcid":"https://orcid.org/0000-0002-1511-1833"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bonati, Leonardo","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039775291","display_name":"Gwenael Poitau","orcid":"https://orcid.org/0000-0002-3675-4176"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Poitau, Gwenael","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101435366","display_name":"M. J. R. Healy","orcid":"https://orcid.org/0000-0002-3879-6513"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Healy, Michael","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009335409","display_name":"Mohammad Alavirad","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Alavirad, Mohammad","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5054337759","display_name":"Tommaso Melodia","orcid":"https://orcid.org/0000-0002-2719-1789"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Melodia, Tommaso","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5063193816"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12784","display_name":"Modular Robots and Swarm Intelligence","score":0.7486000061035156,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T12784","display_name":"Modular Robots and Swarm Intelligence","score":0.7486000061035156,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T10462","display_name":"Reinforcement Learning in Robotics","score":0.7283999919891357,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/ran","display_name":"Ran","score":0.7798765301704407},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6717862486839294},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5507149696350098},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38687247037887573},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.0686405599117279}],"concepts":[{"id":"https://openalex.org/C160704184","wikidata":"https://www.wikidata.org/wiki/Q18031028","display_name":"Ran","level":2,"score":0.7798765301704407},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6717862486839294},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5507149696350098},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38687247037887573},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0686405599117279}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2407.11747","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2407.11747","pdf_url":"https://arxiv.org/pdf/2407.11747","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2407.11747","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2407.11747","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2407.11747","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2407.11747","pdf_url":"https://arxiv.org/pdf/2407.11747","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4403762125.pdf","grobid_xml":"https://content.openalex.org/works/W4403762125.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W1766728438","https://openalex.org/W1668090144","https://openalex.org/W2504993638","https://openalex.org/W2083168956","https://openalex.org/W2980853820","https://openalex.org/W404373762","https://openalex.org/W2186004379"],"abstract_inverted_index":{"The":[0],"highly":[1],"heterogeneous":[2,115],"ecosystem":[3],"of":[4,76,227,237],"NextG":[5],"wireless":[6,169],"communication":[7],"systems":[8],"calls":[9],"for":[10,155],"novel":[11],"networking":[12],"paradigms":[13],"where":[14],"functionalities":[15],"and":[16,21,33,36,43,69,80,84,118,151,163,188,191,212,217,240,252,264],"operations":[17],"can":[18,243,258],"be":[19],"dynamically":[20,100],"optimally":[22],"reconfigured":[23],"in":[24,99,110,166,215],"real":[25],"time":[26],"to":[27,29,55,106,148,195,248],"adapt":[28],"changing":[30],"traffic":[31,211],"conditions":[32,251],"satisfy":[34],"stringent":[35],"diverse":[37,210],"QoS":[38],"demands.":[39],"Open":[40,156],"RAN":[41,63,157,229],"technologies,":[42],"specifically":[44],"those":[45],"being":[46],"standardized":[47],"by":[48,262,269],"the":[49,60,77,129,167,193,206,228,249],"O-RAN":[50,102],"Alliance,":[51],"make":[52],"it":[53],"possible":[54],"integrate":[56],"network":[57,78,82,170,199,245,250],"intelligence":[58],"into":[59],"once":[61],"monolithic":[62],"via":[64],"intelligent":[65,88],"applications,":[66,158],"namely,":[67],"xApps":[68,162,175],"rApps.":[70],"These":[71],"applications":[72],"enable":[73],"flexible":[74],"control":[75,89,197,230],"resources":[79],"functionalities,":[81],"management,":[83],"orchestration":[85],"through":[86],"data-driven":[87],"loops.":[90],"Recent":[91],"work":[92],"has":[93],"showed":[94],"how":[95,105,224],"DRL":[96,132,153,178,241],"is":[97,123],"effective":[98],"controlling":[101],"systems.":[103],"However,":[104],"design":[107,150],"these":[108,203],"solutions":[109],"a":[111,137,146],"way":[112],"that":[113,176],"manages":[114],"optimization":[116],"goals":[117],"prevents":[119],"unfair":[120],"resource":[121],"allocation":[122],"still":[124],"an":[125],"open":[126],"challenge,":[127],"with":[128,192],"logic":[130],"within":[131],"agents":[133,154,179,204],"often":[134],"considered":[135],"as":[136,161,232,234],"black":[138],"box.":[139],"In":[140],"this":[141],"paper,":[142],"we":[143],"introduce":[144],"PandORA,":[145],"framework":[147],"automatically":[149],"train":[152],"package":[159],"them":[160,165],"evaluate":[164],"Colosseum":[168,207],"emulator.":[171],"We":[172,201],"benchmark":[173],"$23$":[174],"embed":[177],"trained":[180],"using":[181],"different":[182,198],"architectures,":[183],"reward":[184,238],"design,":[185],"action":[186],"spaces,":[187],"decision-making":[189,256],"timescales,":[190],"ability":[194],"hierarchically":[196],"parameters.":[200],"test":[202],"on":[205],"testbed":[208],"under":[209],"channel":[213],"conditions,":[214],"static":[216],"mobile":[218],"setups.":[219],"Our":[220],"experimental":[221],"results":[222],"indicate":[223],"suitable":[225],"fine-tuning":[226],"timers,":[231],"well":[233],"proper":[235],"selection":[236],"designs":[239],"architectures":[242],"boost":[244],"performance":[246,261],"according":[247],"demand.":[253],"Notably,":[254],"finer":[255],"granularities":[257],"improve":[259],"mMTC's":[260],"~56%":[263],"even":[265],"increase":[266],"eMBB":[267],"Throughput":[268],"~99%.":[270]},"counts_by_year":[],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2024-10-26T00:00:00"}
