{"id":"https://openalex.org/W7131626531","doi":"https://doi.org/10.1109/rif68108.2025.11406768","title":"Snakes in the Spectrum: Deep and Graph Reinforcement Learning Optimizers for Cognitive Radio Networks","display_name":"Snakes in the Spectrum: Deep and Graph Reinforcement Learning Optimizers for Cognitive Radio Networks","publication_year":2025,"publication_date":"2025-12-08","ids":{"openalex":"https://openalex.org/W7131626531","doi":"https://doi.org/10.1109/rif68108.2025.11406768"},"language":null,"primary_location":{"id":"doi:10.1109/rif68108.2025.11406768","is_oa":false,"landing_page_url":"https://doi.org/10.1109/rif68108.2025.11406768","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Conference on Research in Computing at Feminine (RIF)","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/A5019644262","display_name":"Haider Farhi","orcid":null},"institutions":[{"id":"https://openalex.org/I125485651","display_name":"University Fr\u00e8res Mentouri Constantine 1","ror":"https://ror.org/017wv6808","country_code":"DZ","type":"education","lineage":["https://openalex.org/I125485651"]},{"id":"https://openalex.org/I4210160465","display_name":"Universit\u00e9 Constantine 2","ror":"https://ror.org/056mctw68","country_code":"DZ","type":"education","lineage":["https://openalex.org/I4210160465"]}],"countries":["DZ"],"is_corresponding":false,"raw_author_name":"Haider Farhi","raw_affiliation_strings":["University of Constantine 1,SIACIO Lab,Constantine,Algeria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Constantine 1,SIACIO Lab,Constantine,Algeria","institution_ids":["https://openalex.org/I125485651","https://openalex.org/I4210160465"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048425579","display_name":"Abderraouf Messai","orcid":null},"institutions":[{"id":"https://openalex.org/I125485651","display_name":"University Fr\u00e8res Mentouri Constantine 1","ror":"https://ror.org/017wv6808","country_code":"DZ","type":"education","lineage":["https://openalex.org/I125485651"]},{"id":"https://openalex.org/I4210160465","display_name":"Universit\u00e9 Constantine 2","ror":"https://ror.org/056mctw68","country_code":"DZ","type":"education","lineage":["https://openalex.org/I4210160465"]}],"countries":["DZ"],"is_corresponding":false,"raw_author_name":"Abderraouf Messai","raw_affiliation_strings":["University of Constantine 1,SIACIO Lab,Constantine,Algeria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Constantine 1,SIACIO Lab,Constantine,Algeria","institution_ids":["https://openalex.org/I125485651","https://openalex.org/I4210160465"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010871120","display_name":"Tarek BERGHOUT","orcid":null},"institutions":[{"id":"https://openalex.org/I162489102","display_name":"University of Batna 1","ror":"https://ror.org/04hrbe508","country_code":"DZ","type":"education","lineage":["https://openalex.org/I162489102"]}],"countries":["DZ"],"is_corresponding":false,"raw_author_name":"Tarek Berghout","raw_affiliation_strings":["University of Batna 2,Department of Industrial Engineering,Batna,Algeria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Batna 2,Department of Industrial Engineering,Batna,Algeria","institution_ids":["https://openalex.org/I162489102"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.69489646,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"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":0.5995000004768372,"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":0.5995000004768372,"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":0.09640000015497208,"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/T12131","display_name":"Wireless Signal Modulation Classification","score":0.0674000009894371,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.8999000191688538},{"id":"https://openalex.org/keywords/cognitive-radio","display_name":"Cognitive radio","score":0.7935000061988831},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6362000107765198},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.46560001373291016},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.41839998960494995},{"id":"https://openalex.org/keywords/collision","display_name":"Collision","score":0.3831999897956848},{"id":"https://openalex.org/keywords/frequency-allocation","display_name":"Frequency allocation","score":0.3693999946117401},{"id":"https://openalex.org/keywords/channel-allocation-schemes","display_name":"Channel allocation schemes","score":0.35659998655319214},{"id":"https://openalex.org/keywords/q-learning","display_name":"Q-learning","score":0.3391999900341034}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8999000191688538},{"id":"https://openalex.org/C149946192","wikidata":"https://www.wikidata.org/wiki/Q3235733","display_name":"Cognitive radio","level":3,"score":0.7935000061988831},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7353000044822693},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6362000107765198},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.532800018787384},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.46560001373291016},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.41839998960494995},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4171999990940094},{"id":"https://openalex.org/C121704057","wikidata":"https://www.wikidata.org/wiki/Q352070","display_name":"Collision","level":2,"score":0.3831999897956848},{"id":"https://openalex.org/C134579502","wikidata":"https://www.wikidata.org/wiki/Q1455619","display_name":"Frequency allocation","level":2,"score":0.3693999946117401},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3580000102519989},{"id":"https://openalex.org/C114237682","wikidata":"https://www.wikidata.org/wiki/Q5072483","display_name":"Channel allocation schemes","level":3,"score":0.35659998655319214},{"id":"https://openalex.org/C188116033","wikidata":"https://www.wikidata.org/wiki/Q2664563","display_name":"Q-learning","level":3,"score":0.3391999900341034},{"id":"https://openalex.org/C109718341","wikidata":"https://www.wikidata.org/wiki/Q1385229","display_name":"Metaheuristic","level":2,"score":0.3246000111103058},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.3181999921798706},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.31470000743865967},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.3124000132083893},{"id":"https://openalex.org/C3020442560","wikidata":"https://www.wikidata.org/wiki/Q4971815","display_name":"Broad spectrum","level":2,"score":0.3093000054359436},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3059999942779541},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2953999936580658},{"id":"https://openalex.org/C57869625","wikidata":"https://www.wikidata.org/wiki/Q1783502","display_name":"Rate of convergence","level":3,"score":0.27720001339912415},{"id":"https://openalex.org/C74072328","wikidata":"https://www.wikidata.org/wiki/Q1142726","display_name":"Intelligent agent","level":2,"score":0.2623000144958496},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.25699999928474426},{"id":"https://openalex.org/C137246740","wikidata":"https://www.wikidata.org/wiki/Q583970","display_name":"Spectral efficiency","level":3,"score":0.25609999895095825},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.25200000405311584},{"id":"https://openalex.org/C2780864053","wikidata":"https://www.wikidata.org/wiki/Q5147495","display_name":"Collision avoidance","level":3,"score":0.25200000405311584}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/rif68108.2025.11406768","is_oa":false,"landing_page_url":"https://doi.org/10.1109/rif68108.2025.11406768","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Conference on Research in Computing at Feminine (RIF)","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":12,"referenced_works":["https://openalex.org/W4286893914","https://openalex.org/W4307405860","https://openalex.org/W4313362273","https://openalex.org/W4322631215","https://openalex.org/W4388969755","https://openalex.org/W4389495985","https://openalex.org/W4396240995","https://openalex.org/W4401980060","https://openalex.org/W4408412999","https://openalex.org/W4411568266","https://openalex.org/W4412766252","https://openalex.org/W4414020669"],"related_works":[],"abstract_inverted_index":{"Efficient":[0],"spectrum":[1,184],"allocation":[2,169],"in":[3,168,182],"Cognitive":[4],"Radio":[5],"Networks":[6],"(CRNs)":[7],"remains":[8],"a":[9,81,165],"persistent":[10],"challenge":[11],"due":[12],"to":[13,35,46,114],"the":[14,48,60,63],"dynamic":[15,183],"activity":[16],"of":[17,62],"Primary":[18],"Users":[19,26],"(PUs)":[20],"and":[21,53,74,89,99,117,151,171],"potential":[22],"collisions":[23],"with":[24,67,129,176],"Secondary":[25],"(SUs).":[27],"Reinforcement":[28,76],"Learning":[29,77],"(RL)":[30],"has":[31],"been":[32],"increasingly":[33],"applied":[34],"address":[36],"this":[37,56],"issue;":[38],"however,":[39],"conventional":[40],"deep":[41],"learning":[42],"models":[43],"often":[44],"struggle":[45],"capture":[47],"relational":[49],"structure":[50],"among":[51],"users":[52],"channels.":[54],"In":[55],"study,":[57],"we":[58],"investigate":[59],"integration":[61],"Snake":[64],"Optimizer":[65],"(SO)":[66],"two":[68],"RL":[69,104,175],"paradigms:":[70],"Deep":[71],"Q-Networks":[72],"(DQN)":[73],"Graph-based":[75],"(DGRL).":[78],"We":[79],"implement":[80],"CRN":[82],"environment":[83],"comprising":[84],"five":[85],"PUs,":[86],"ten":[87],"SUs,":[88],"fifteen":[90],"channels,":[91],"optimizing":[92],"Spectrum":[93],"Utilization":[94],"Efficiency":[95],"(SUE),":[96],"collision":[97,146],"rate,":[98],"spectral":[100],"capacity":[101],"(SC).":[102],"Each":[103],"agent":[105],"proposes":[106],"channel":[107],"allocations":[108],"that":[109,123,159,172],"are":[110],"refined":[111],"using":[112],"SO":[113],"enhance":[115],"convergence":[116],"reduce":[118],"collisions.":[119],"Comparative":[120],"experiments":[121],"demonstrate":[122],"both":[124],"approaches":[125],"achieve":[126],"high":[127],"performance,":[128,170],"DGRL+SO":[130],"slightly":[131],"outperforming":[132],"DQN+SO":[133],"across":[134],"all":[135],"metrics:":[136],"average":[137],"reward":[138],"(0.4621":[139],"vs.":[140,144,149,154],"0.4586),":[141],"SUE":[142],"(66.27%":[143],"65.97%),":[145],"rate":[147],"(0.0060":[148],"0.0105),":[150],"SC":[152],"(9.940":[153],"9.895).":[155],"These":[156],"results":[157],"indicate":[158],"modeling":[160],"CRNs":[161],"as":[162],"graphs":[163],"provides":[164],"measurable":[166],"advantage":[167],"combining":[173],"graph-aware":[174],"metaheuristic":[177],"optimization":[178],"can":[179],"improve":[180],"robustness":[181],"access":[185],"scenarios.":[186]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-02-27T00:00:00"}
