{"id":"https://openalex.org/W4205394534","doi":"https://doi.org/10.1109/uemcon53757.2021.9666500","title":"Sum rate maximization of D2D networks with energy constrained UAVs through deep unsupervised learning","display_name":"Sum rate maximization of D2D networks with energy constrained UAVs through deep unsupervised learning","publication_year":2021,"publication_date":"2021-12-01","ids":{"openalex":"https://openalex.org/W4205394534","doi":"https://doi.org/10.1109/uemcon53757.2021.9666500"},"language":"en","primary_location":{"id":"doi:10.1109/uemcon53757.2021.9666500","is_oa":false,"landing_page_url":"https://doi.org/10.1109/uemcon53757.2021.9666500","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 12th Annual Ubiquitous Computing, Electronics &amp; Mobile Communication Conference (UEMCON)","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/A5004682361","display_name":"Benjamin Lea","orcid":null},"institutions":[{"id":"https://openalex.org/I160262251","display_name":"Thompson Rivers University","ror":"https://ror.org/01v9wj339","country_code":"CA","type":"education","lineage":["https://openalex.org/I160262251"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Benjamin Lea","raw_affiliation_strings":["Department of Engineering, Thompson Rivers University (TRU), Kamloops, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Engineering, Thompson Rivers University (TRU), Kamloops, Canada","institution_ids":["https://openalex.org/I160262251"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082912094","display_name":"Debaditya Shome","orcid":"https://orcid.org/0000-0001-9168-0379"},"institutions":[{"id":"https://openalex.org/I67357951","display_name":"KIIT University","ror":"https://ror.org/00k8zt527","country_code":"IN","type":"education","lineage":["https://openalex.org/I67357951"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Debaditya Shome","raw_affiliation_strings":["School of Electronics Engineering, KIIT University, Odisha, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronics Engineering, KIIT University, Odisha, India","institution_ids":["https://openalex.org/I67357951"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035909356","display_name":"Omer Waqar","orcid":"https://orcid.org/0000-0003-1787-7100"},"institutions":[{"id":"https://openalex.org/I160262251","display_name":"Thompson Rivers University","ror":"https://ror.org/01v9wj339","country_code":"CA","type":"education","lineage":["https://openalex.org/I160262251"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Omer Waqar","raw_affiliation_strings":["Department of Engineering, Thompson Rivers University (TRU), Kamloops, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Engineering, Thompson Rivers University (TRU), Kamloops, Canada","institution_ids":["https://openalex.org/I160262251"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054866227","display_name":"Jabed Tomal","orcid":"https://orcid.org/0000-0001-9953-3744"},"institutions":[{"id":"https://openalex.org/I160262251","display_name":"Thompson Rivers University","ror":"https://ror.org/01v9wj339","country_code":"CA","type":"education","lineage":["https://openalex.org/I160262251"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Jabed Tomal","raw_affiliation_strings":["Department of Mathematics and Statistics, Thompson Rivers University (TRU), Kamloops, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, Thompson Rivers University (TRU), Kamloops, Canada","institution_ids":["https://openalex.org/I160262251"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.3945,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.95518679,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"0453","last_page":"0459"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11133","display_name":"UAV Applications and Optimization","score":0.9998999834060669,"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":0.9998999834060669,"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/T11392","display_name":"Energy Harvesting in Wireless Networks","score":0.9995999932289124,"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/T11458","display_name":"Advanced Wireless Communication Technologies","score":0.9976999759674072,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.780038595199585},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.7005748152732849},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.6811800599098206},{"id":"https://openalex.org/keywords/coherence","display_name":"Coherence (philosophical gambling strategy)","score":0.6158182621002197},{"id":"https://openalex.org/keywords/coherence-time","display_name":"Coherence time","score":0.6020691394805908},{"id":"https://openalex.org/keywords/drone","display_name":"Drone","score":0.5599542260169983},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.5590022802352905},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.5121293067932129},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.49822139739990234},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4967120289802551},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.475132018327713},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.449678897857666},{"id":"https://openalex.org/keywords/transmitter-power-output","display_name":"Transmitter power output","score":0.44697344303131104},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.41693946719169617},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.39391404390335083},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3923470973968506},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3885899484157562},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.18587011098861694},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.10525119304656982},{"id":"https://openalex.org/keywords/transmitter","display_name":"Transmitter","score":0.08512216806411743},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08505544066429138}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.780038595199585},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.7005748152732849},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.6811800599098206},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.6158182621002197},{"id":"https://openalex.org/C47091857","wikidata":"https://www.wikidata.org/wiki/Q4118612","display_name":"Coherence time","level":3,"score":0.6020691394805908},{"id":"https://openalex.org/C59519942","wikidata":"https://www.wikidata.org/wiki/Q650665","display_name":"Drone","level":2,"score":0.5599542260169983},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5590022802352905},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.5121293067932129},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.49822139739990234},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4967120289802551},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.475132018327713},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.449678897857666},{"id":"https://openalex.org/C65422117","wikidata":"https://www.wikidata.org/wiki/Q358527","display_name":"Transmitter power output","level":4,"score":0.44697344303131104},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.41693946719169617},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.39391404390335083},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3923470973968506},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3885899484157562},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.18587011098861694},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.10525119304656982},{"id":"https://openalex.org/C47798520","wikidata":"https://www.wikidata.org/wiki/Q190157","display_name":"Transmitter","level":3,"score":0.08512216806411743},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08505544066429138},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/uemcon53757.2021.9666500","is_oa":false,"landing_page_url":"https://doi.org/10.1109/uemcon53757.2021.9666500","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 12th Annual Ubiquitous Computing, Electronics &amp; Mobile Communication Conference (UEMCON)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.8999999761581421}],"awards":[],"funders":[{"id":"https://openalex.org/F4320307908","display_name":"Thompson","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2302104218","https://openalex.org/W2473185587","https://openalex.org/W2746411854","https://openalex.org/W2850930826","https://openalex.org/W2886509985","https://openalex.org/W2890592307","https://openalex.org/W2962804513","https://openalex.org/W2963061782","https://openalex.org/W2992716901","https://openalex.org/W2994008524","https://openalex.org/W3003307790","https://openalex.org/W3046174374","https://openalex.org/W3093648387","https://openalex.org/W3095931495","https://openalex.org/W3177911636","https://openalex.org/W3192277190","https://openalex.org/W6800191630"],"related_works":["https://openalex.org/W4229448053","https://openalex.org/W2059768187","https://openalex.org/W4247925126","https://openalex.org/W4312858960","https://openalex.org/W4386036939","https://openalex.org/W4327774218","https://openalex.org/W3206445629","https://openalex.org/W2605096541","https://openalex.org/W3200286695","https://openalex.org/W4379143281"],"abstract_inverted_index":{"We":[0],"consider":[1],"a":[2,83,88,119,129,177],"system":[3,29,70],"model":[4],"in":[5,78,127],"which":[6,45,128],"several":[7],"energy":[8,59],"harvesting":[9],"(EH)":[10],"unmanned":[11],"aerial":[12],"vehicles":[13],"(UAVs),":[14],"often":[15],"known":[16],"as":[17,96],"drones,":[18],"are":[19,94,101,107],"deployed":[20],"with":[21],"device-to-device":[22],"(D2D)":[23],"communication":[24],"networks.":[25],"For":[26],"the":[27,47,51,57,62,66,69,137],"considered":[28],"model,":[30,71],"we":[31,113],"formulate":[32],"an":[33,40,159],"optimization":[34,92],"problem":[35,116],"that":[36,146],"aims":[37],"to":[38,75,153,170],"find":[39],"optimal":[41],"transmit":[42],"power":[43,139],"vector":[44],"maximizes":[46],"sum":[48,156],"rate":[49,157],"of":[50,61,65,68],"D2D":[52],"network":[53,132],"while":[54],"also":[55],"meets":[56],"minimum":[58],"requirements":[60],"UAVs.":[63],"Because":[64],"nature":[67],"it":[72],"is":[73,134,142,168],"necessary":[74],"deliver":[76],"solutions":[77,106,172],"real":[79],"time":[80],"i.e.,":[81,175],"within":[82,176],"channel":[84,178],"coherence":[85,179],"time.":[86,180],"As":[87],"result,":[89],"conventional":[90],"non-data-driven":[91],"methods":[93],"inapplicable,":[95],"either":[97],"their":[98,105],"run-time":[99],"overheads":[100],"prohibitively":[102],"expensive":[103],"or":[104],"significantly":[108],"suboptimal.":[109],"In":[110],"this":[111,115],"paper,":[112],"address":[114],"by":[117,136],"proposing":[118],"deep":[120,130],"unsupervised":[121],"learning":[122],"(DUL)":[123],"based":[124],"hybrid":[125,149],"scheme":[126,150,164,167],"neural":[131],"(DNN)":[133],"complemented":[135],"full":[138],"scheme.":[140],"It":[141],"shown":[143],"through":[144],"simulations":[145],"our":[147,166],"proposed":[148],"provides":[151],"up":[152],"91%":[154],"higher":[155],"than":[158],"existing":[160],"fully":[161],"non-data":[162],"driven":[163],"and":[165],"able":[169],"obtain":[171],"quite":[173],"efficiently,":[174]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
