{"id":"https://openalex.org/W4404563332","doi":"https://doi.org/10.1109/lcomm.2024.3504372","title":"UAV-Assisted NOMA for Enhancing ISAC: A Deep Reinforcement Learning Solution","display_name":"UAV-Assisted NOMA for Enhancing ISAC: A Deep Reinforcement Learning Solution","publication_year":2024,"publication_date":"2024-11-20","ids":{"openalex":"https://openalex.org/W4404563332","doi":"https://doi.org/10.1109/lcomm.2024.3504372"},"language":"en","primary_location":{"id":"doi:10.1109/lcomm.2024.3504372","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lcomm.2024.3504372","pdf_url":null,"source":{"id":"https://openalex.org/S147316732","display_name":"IEEE Communications Letters","issn_l":"1089-7798","issn":["1089-7798","1558-2558","2373-7891"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310316002","host_organization_name":"IEEE Communications Society","host_organization_lineage":["https://openalex.org/P4310316002","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Communications Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Communications Letters","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/A5094001431","display_name":"Ali Amhaz","orcid":"https://orcid.org/0009-0000-2290-8253"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Ali Amhaz","raw_affiliation_strings":["CIISE, Concordia University, Montreal, QC, Canada"],"raw_orcid":"https://orcid.org/0009-0000-2290-8253","affiliations":[{"raw_affiliation_string":"CIISE, Concordia University, Montreal, QC, Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059101599","display_name":"Mohamed Elhattab","orcid":"https://orcid.org/0000-0001-7682-9972"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Mohamed Elhattab","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Concordia University, Montreal, QC, Canada"],"raw_orcid":"https://orcid.org/0000-0001-7682-9972","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Concordia University, Montreal, QC, Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071725114","display_name":"Sanaa Sharafeddine","orcid":"https://orcid.org/0000-0001-6548-1624"},"institutions":[{"id":"https://openalex.org/I98635879","display_name":"American University of Beirut","ror":"https://ror.org/04pznsd21","country_code":"LB","type":"education","lineage":["https://openalex.org/I98635879"]}],"countries":["LB"],"is_corresponding":false,"raw_author_name":"Sanaa Sharafeddine","raw_affiliation_strings":["Department of Electrical and Computer Engineering, American University of Beirut, Beirut, Lebanon"],"raw_orcid":"https://orcid.org/0000-0001-6548-1624","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, American University of Beirut, Beirut, Lebanon","institution_ids":["https://openalex.org/I98635879"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072393948","display_name":"Chadi Assi","orcid":"https://orcid.org/0000-0002-3161-1846"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Chadi Assi","raw_affiliation_strings":["Concordia Institute for Information Systems Engineering (CIISE), Concordia University, Montreal, QC, Canada"],"raw_orcid":"https://orcid.org/0000-0002-3161-1846","affiliations":[{"raw_affiliation_string":"Concordia Institute for Information Systems Engineering (CIISE), Concordia University, Montreal, QC, Canada","institution_ids":["https://openalex.org/I60158472"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5094001431"],"corresponding_institution_ids":["https://openalex.org/I60158472"],"apc_list":null,"apc_paid":null,"fwci":12.2949,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.98068789,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"29","issue":"2","first_page":"249","last_page":"253"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11133","display_name":"UAV Applications and Optimization","score":0.9717000126838684,"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"}},"topics":[{"id":"https://openalex.org/T11133","display_name":"UAV Applications and Optimization","score":0.9717000126838684,"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"}},{"id":"https://openalex.org/T11192","display_name":"Underwater Vehicles and Communication Systems","score":0.9631999731063843,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/T10036","display_name":"Advanced Neural Network Applications","score":0.9491999745368958,"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/noma","display_name":"Noma","score":0.8846437931060791},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.746669352054596},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7168912887573242},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.3499992787837982},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.3399254083633423},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3180351257324219},{"id":"https://openalex.org/keywords/telecommunications-link","display_name":"Telecommunications link","score":0.2829664349555969}],"concepts":[{"id":"https://openalex.org/C2775918612","wikidata":"https://www.wikidata.org/wiki/Q994794","display_name":"Noma","level":3,"score":0.8846437931060791},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.746669352054596},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7168912887573242},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.3499992787837982},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.3399254083633423},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3180351257324219},{"id":"https://openalex.org/C138660444","wikidata":"https://www.wikidata.org/wiki/Q5607897","display_name":"Telecommunications link","level":2,"score":0.2829664349555969}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lcomm.2024.3504372","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lcomm.2024.3504372","pdf_url":null,"source":{"id":"https://openalex.org/S147316732","display_name":"IEEE Communications Letters","issn_l":"1089-7798","issn":["1089-7798","1558-2558","2373-7891"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310316002","host_organization_name":"IEEE Communications Society","host_organization_lineage":["https://openalex.org/P4310316002","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Communications Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Communications Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321588","display_name":"Concordia University","ror":"https://ror.org/0420zvk78"},{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W2943017603","https://openalex.org/W2964202652","https://openalex.org/W3034281970","https://openalex.org/W3042876727","https://openalex.org/W3109039904","https://openalex.org/W4226212088","https://openalex.org/W4312809892","https://openalex.org/W4320919486","https://openalex.org/W4361801860","https://openalex.org/W4367277145","https://openalex.org/W4385694480","https://openalex.org/W4392152236","https://openalex.org/W4394910879","https://openalex.org/W4399168643","https://openalex.org/W4400770877","https://openalex.org/W4401567650","https://openalex.org/W4401634169","https://openalex.org/W6857188491"],"related_works":["https://openalex.org/W3030525848","https://openalex.org/W4385197910","https://openalex.org/W2340639785","https://openalex.org/W4404253608","https://openalex.org/W3010814398","https://openalex.org/W4385197899","https://openalex.org/W3005957545","https://openalex.org/W2076432172","https://openalex.org/W4309235375","https://openalex.org/W2887349183"],"abstract_inverted_index":{"This":[0],"letter":[1],"examines":[2],"a":[3,73,128],"NOMA":[4],"downlink":[5],"scenario":[6],"where":[7],"the":[8,28,32,43,50,58,62,98,102,107,110,114,118,121,142,148,151,160,166],"UAV":[9,44,156],"is":[10],"deployed":[11],"to":[12,41,88,93,113,139,162],"concurrently":[13],"assist":[14],"in":[15,76,109],"communication":[16,68],"and":[17,26,46,54,70,91,117,159],"sensing":[18,71],"functionalities,":[19],"empowering":[20],"ISAC":[21],"technology.":[22],"In":[23],"this":[24],"regard":[25],"with":[27,141],"goal":[29],"of":[30,64,78,97,120,150],"maximizing":[31],"average":[33],"achievable":[34],"rate,":[35],"we":[36,126],"formulate":[37],"an":[38],"optimization":[39],"problem":[40,86],"determine":[42],"trajectory,":[45],"beamforming":[47],"vectors":[48],"at":[49,57],"transmitting":[51],"base":[52],"station":[53],"UAV,":[55],"while":[56],"same":[59],"time":[60],"satisfy":[61],"quality":[63],"service":[65],"constraints":[66],"for":[67,72],"users":[69],"moving":[74],"target":[75],"terms":[77],"Cramer":[79],"Rao":[80],"bound":[81],"(CRB)":[82],"metric.":[83],"The":[84],"formulated":[85],"showed":[87],"be":[89,94],"non-convex":[90],"hard":[92],"solved":[95],"because":[96],"high":[99],"coupling":[100],"between":[101],"variables":[103],"as":[104,106],"well":[105],"randomness":[108],"environment":[111],"due":[112],"channels":[115],"variations":[116],"mobility":[119],"target.":[122],"For":[123],"that":[124],"reason,":[125],"adopted":[127],"reinforcement":[129],"learning":[130],"algorithm,":[131],"namely,":[132],"deep":[133],"deterministic":[134],"policy":[135],"gradient":[136],"(DDPG)":[137],"approach":[138],"deal":[140],"aforementioned":[143],"problems.":[144],"Numerical":[145],"results":[146],"proved":[147],"superiority":[149],"presented":[152],"model":[153],"over":[154],"traditional":[155],"trajectory":[157],"benchmarks":[158],"ability":[161],"gain":[163],"knowledge":[164],"from":[165],"environment.":[167]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":6}],"updated_date":"2025-12-23T23:11:35.936235","created_date":"2025-10-10T00:00:00"}