{"id":"https://openalex.org/W7212422754","doi":"https://doi.org/10.1016/j.rico.2026.100823","title":"Hybrid GRU\u2013LSTM\u2013CNN deep learning model for cooperative spectrum sensing in cognitive radio networks","display_name":"Hybrid GRU\u2013LSTM\u2013CNN deep learning model for cooperative spectrum sensing in cognitive radio networks","publication_year":2026,"publication_date":"2026-09-13","ids":{"openalex":"https://openalex.org/W7212422754","doi":"https://doi.org/10.1016/j.rico.2026.100823"},"language":"en","primary_location":{"id":"doi:10.1016/j.rico.2026.100823","doi":"https://doi.org/10.1016/j.rico.2026.100823","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.rico.2026.100823","pdf_url":"https://www.sciencedirect.com/science/article/pii/S266672072600175X/pdf","source":{"id":"https://openalex.org/S4210182769","display_name":"Results in Control and Optimization","issn_l":"2666-7207","issn":["2666-7207"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","dongbi-d","oarl","poland-20"],"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Results in Control and Optimization","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.sciencedirect.com/science/article/pii/S266672072600175X/pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5151604602","display_name":"Arun Kumar","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I81433678","display_name":"Sikkim Manipal University","ror":"https://ror.org/010gckf65","country_code":"IN","type":"education","lineage":["https://openalex.org/I81433678"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Arun Kumar","raw_affiliation_strings":["Department of Electronics and Communication Engineering, Sikkim Manipal Institute of Technology, Sikkim Manipal University, Rangpo, Majitar, Sikkim, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronics and Communication Engineering, Sikkim Manipal Institute of Technology, Sikkim Manipal University, Rangpo, Majitar, Sikkim, India","institution_ids":["https://openalex.org/I81433678"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104078766","display_name":"Mehedi Masud","orcid":"https://orcid.org/0000-0001-6019-7245","observed_orcids":["https://orcid.org/0000-0001-6019-7245"]},"institutions":[{"id":"https://openalex.org/I179331831","display_name":"Taif University","ror":"https://ror.org/014g1a453","country_code":"SA","type":"education","lineage":["https://openalex.org/I179331831"]},{"id":"https://openalex.org/I45998257","display_name":"Sohar University","ror":"https://ror.org/02ftvf862","country_code":"OM","type":"education","lineage":["https://openalex.org/I45998257"]}],"countries":["OM","SA"],"is_corresponding":false,"raw_author_name":"Mehedi Masud","raw_affiliation_strings":["Department of Computer Science, College of Computers and Information Technology, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia","Faculty of Computing and IT, Sohar University, P.O. Box 44., PC. 311, Sohar, Oman"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, College of Computers and Information Technology, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia","institution_ids":["https://openalex.org/I179331831"]},{"raw_affiliation_string":"Faculty of Computing and IT, Sohar University, P.O. Box 44., PC. 311, Sohar, Oman","institution_ids":["https://openalex.org/I45998257"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102823492","display_name":"Nishant Gaur","orcid":"https://orcid.org/0000-0002-2819-1465","observed_orcids":["https://orcid.org/0000-0002-2819-1465"]},"institutions":[{"id":"https://openalex.org/I3131927718","display_name":"JECRC University","ror":"https://ror.org/04hjsag95","country_code":"IN","type":"education","lineage":["https://openalex.org/I3131927718"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Nishant Gaur","raw_affiliation_strings":["Department of Physics, JECRC University, Jaipur, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Physics, JECRC University, Jaipur, India","institution_ids":["https://openalex.org/I3131927718"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089916394","display_name":"Aziz Nanthaamornphong","orcid":"https://orcid.org/0000-0002-1618-6001","observed_orcids":["https://orcid.org/0000-0002-1618-6001"]},"institutions":[{"id":"https://openalex.org/I131868736","display_name":"Prince of Songkla University","ror":"https://ror.org/0575ycz84","country_code":"TH","type":"education","lineage":["https://openalex.org/I131868736"]}],"countries":["TH"],"is_corresponding":true,"raw_author_name":"Aziz Nanthaamornphong","raw_affiliation_strings":["College of Computing, Prince of Songkla University, Phuket, Thailand"],"raw_orcid":"https://orcid.org/0000-0002-1618-6001","affiliations":[{"raw_affiliation_string":"College of Computing, Prince of Songkla University, Phuket, Thailand","institution_ids":["https://openalex.org/I131868736"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5089916394"],"corresponding_institution_ids":["https://openalex.org/I131868736"],"apc_list":{"value":1470,"currency":"USD","value_usd":1470},"apc_paid":{"value":1470,"currency":"USD","value_usd":1470},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"25","issue":null,"first_page":"100823","last_page":"100823"},"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":1.0,"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":1.0,"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/T12131","display_name":"Wireless Signal Modulation Classification","score":0.0,"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/T10891","display_name":"Radar Systems and Signal Processing","score":0.0,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cooperative-spectrum-sensing","display_name":"cooperative spectrum sensing","score":0.9480000138282776},{"id":"https://openalex.org/keywords/cognitive-radio-networks","display_name":"cognitive radio networks","score":0.9559999704360962},{"id":"https://openalex.org/keywords/monte-carlo-dropout","display_name":"Monte Carlo dropout","score":0.6959999799728394},{"id":"https://openalex.org/keywords/adaptive-fusion","display_name":"adaptive fusion","score":0.5180000066757202},{"id":"https://openalex.org/keywords/spectrum-sensing-data-falsification-attack","display_name":"spectrum sensing data falsification attack","score":0.9089999794960022},{"id":"https://openalex.org/keywords/primary-user-detection","display_name":"primary user detection","score":0.7409999966621399},{"id":"https://openalex.org/keywords/rician-fading","display_name":"Rician fading","score":0.7179999947547913},{"id":"https://openalex.org/keywords/communication-overhead-reduction","display_name":"communication cost reduction","score":0.5920000076293945}],"concepts":[{"id":"https://openalex.org/C149946192","wikidata":"https://www.wikidata.org/wiki/Q3235733","display_name":"Cognitive radio","level":3,"score":0.83160001039505},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7649000287055969},{"id":"https://openalex.org/C60472773","wikidata":"https://www.wikidata.org/wiki/Q7331156","display_name":"Rician fading","level":4,"score":0.578499972820282},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.5374000072479248},{"id":"https://openalex.org/C81978471","wikidata":"https://www.wikidata.org/wiki/Q1196572","display_name":"Fading","level":3,"score":0.5230000019073486},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5120999813079834},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47369998693466187},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46950000524520874},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.43389999866485596},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.41990000009536743},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.4198000133037567},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.39250001311302185},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.3628000020980835},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35749998688697815},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.3343000113964081},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.334199994802475},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3224000036716461},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3222000002861023},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3142000138759613},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.3122999966144562},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.28610000014305115},{"id":"https://openalex.org/C108037233","wikidata":"https://www.wikidata.org/wiki/Q11375","display_name":"Wireless network","level":3,"score":0.28360000252723694},{"id":"https://openalex.org/C63029442","wikidata":"https://www.wikidata.org/wiki/Q6504978","display_name":"Spectrum management","level":4,"score":0.27239999175071716},{"id":"https://openalex.org/C101765175","wikidata":"https://www.wikidata.org/wiki/Q577764","display_name":"Communications system","level":2,"score":0.2711000144481659},{"id":"https://openalex.org/C32542511","wikidata":"https://www.wikidata.org/wiki/Q5141225","display_name":"Cognitive network","level":4,"score":0.26899999380111694},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.2623000144958496},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.26089999079704285},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26019999384880066},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.25119999051094055}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1016/j.rico.2026.100823","doi":"https://doi.org/10.1016/j.rico.2026.100823","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.rico.2026.100823","pdf_url":"https://www.sciencedirect.com/science/article/pii/S266672072600175X/pdf","source":{"id":"https://openalex.org/S4210182769","display_name":"Results in Control and Optimization","issn_l":"2666-7207","issn":["2666-7207"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","dongbi-d","oarl","poland-20"],"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Results in Control and Optimization","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:85e36871f9b24d3c87cad7db92682b4e","doi":null,"is_oa":false,"landing_page_url":"https://doaj.org/article/85e36871f9b24d3c87cad7db92682b4e","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Results in Control and Optimization, Vol 25, Iss , Pp 100823- (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1016/j.rico.2026.100823","doi":"https://doi.org/10.1016/j.rico.2026.100823","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.rico.2026.100823","pdf_url":"https://www.sciencedirect.com/science/article/pii/S266672072600175X/pdf","source":{"id":"https://openalex.org/S4210182769","display_name":"Results in Control and Optimization","issn_l":"2666-7207","issn":["2666-7207"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","dongbi-d","oarl","poland-20"],"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Results in Control and Optimization","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320323722","display_name":"Taif University","ror":"https://ror.org/014g1a453"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7212422754.pdf","grobid_xml":"https://content.openalex.org/works/W7212422754.grobid-xml"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W2098623162","https://openalex.org/W2796817989","https://openalex.org/W2943868753","https://openalex.org/W3012061181","https://openalex.org/W3014537413","https://openalex.org/W4313585690","https://openalex.org/W4387223140","https://openalex.org/W4388221189","https://openalex.org/W4388969755","https://openalex.org/W4391983109","https://openalex.org/W4399800816","https://openalex.org/W4400485124","https://openalex.org/W4402246371","https://openalex.org/W4407024721","https://openalex.org/W4408017145","https://openalex.org/W4410770315","https://openalex.org/W4411358691","https://openalex.org/W4411384943","https://openalex.org/W4413155830","https://openalex.org/W4413464929","https://openalex.org/W4414008455","https://openalex.org/W7130940676"],"related_works":["https://openalex.org/W7204996162","https://openalex.org/W7130385921","https://openalex.org/W4205794674","https://openalex.org/W7223090387","https://openalex.org/W4385834069","https://openalex.org/W7140310360","https://openalex.org/W4409046949","https://openalex.org/W7165863894","https://openalex.org/W7117579570","https://openalex.org/W4229457528"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,16,99,211],"reliability-aware":[4],"cooperative":[5],"spectrum":[6],"sensing":[7,61,80],"framework":[8,24,209],"for":[9,30,39,49,217],"Cognitive":[10],"Radio":[11],"(CR)":[12],"networks":[13,38],"based":[14],"on":[15,140,175],"hybrid":[17],"GRU\u2013LSTM\u2013CNN":[18],"deep":[19],"learning":[20],"architecture.":[21],"The":[22,152],"proposed":[23,150,153,208],"integrates":[25],"Convolutional":[26],"Neural":[27],"Networks":[28],"(CNNs)":[29],"spectro-temporal":[31],"feature":[32],"extraction,":[33],"Long":[34],"Short-Term":[35],"Memory":[36],"(LSTM)":[37],"long-term":[40],"temporal":[41],"dependency":[42],"learning,":[43],"and":[44,70,95,132,190,214,221],"Gated":[45],"Recurrent":[46],"Units":[47],"(GRUs)":[48],"efficient":[50],"short-term":[51],"sequential":[52],"modeling.":[53],"Each":[54],"Secondary":[55],"User":[56,66],"(SU)":[57],"generates":[58],"calibrated":[59],"soft":[60,201],"reports":[62],"consisting":[63],"of":[64,148,173,186],"Primary":[65],"(PU)":[67],"detection":[68,157],"probability":[69],"predictive":[71],"uncertainty":[72,96],"obtained":[73],"through":[74],"Monte":[75],"Carlo":[76],"dropout.":[77],"To":[78],"improve":[79],"reliability,":[81],"an":[82,113,171],"adaptive":[83],"fusion":[84,115],"mechanism":[85],"assigns":[86],"reliability":[87],"weights":[88],"according":[89],"to":[90,108],"signal":[91],"quality,":[92],"confidence":[93],"level,":[94],"information.":[97],"Furthermore,":[98],"Straight-Through":[100],"Estimator":[101],"(STE)-based":[102],"quantized":[103],"reporting":[104],"strategy":[105],"is":[106],"introduced":[107],"reduce":[109],"communication":[110,193,224],"overhead,":[111],"while":[112],"outlier-robust":[114],"scheme":[116],"mitigates":[117],"Spectrum":[118],"Sensing":[119],"Data":[120],"Falsification":[121],"(SSDF)":[122],"attacks.":[123],"Extensive":[124],"simulations":[125],"under":[126],"Rician":[127],"fading":[128],"channels":[129],"with":[130,138,198],"15%":[131],"25%":[133],"channel":[134],"estimation":[135],"errors,":[136],"together":[137],"validation":[139],"the":[141,146,149,207],"RadioML":[142,177],"RML2016.10a":[143],"dataset,":[144],"demonstrate":[145],"effectiveness":[147],"framework.":[151],"method":[154],"achieves":[155],"near-perfect":[156],"performance":[158,182],"(Pd":[159],"\u2248":[160],"1)":[161],"at":[162],"SNR":[163],"values":[164],"as":[165,167],"low":[166],"\u22124":[168],"dB,":[169],"attains":[170],"AUC":[172],"0.87":[174],"real-world":[176],"data,":[178],"maintains":[179],"stable":[180],"false-alarm":[181],"even":[183],"when":[184],"30%":[185],"SUs":[187],"are":[188],"malicious,":[189],"reduces":[191],"sensing-report":[192],"overhead":[194],"by":[195],"89\u201397%":[196],"compared":[197],"conventional":[199],"full-precision":[200],"reporting.":[202],"These":[203],"results":[204],"confirm":[205],"that":[206],"provides":[210],"robust,":[212],"communication-efficient,":[213],"scalable":[215],"solution":[216],"next-generation":[218],"CR,":[219],"IoT,":[220],"beyond-5G/6G":[222],"wireless":[223],"systems.":[225]},"counts_by_year":[],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2026-09-14T00:00:00"}