{"id":"https://openalex.org/W3051352583","doi":"https://doi.org/10.1109/twc.2020.3016024","title":"3D UAV Trajectory Design and Frequency Band Allocation for Energy-Efficient and Fair Communication: A Deep Reinforcement Learning Approach","display_name":"3D UAV Trajectory Design and Frequency Band Allocation for Energy-Efficient and Fair Communication: A Deep Reinforcement Learning Approach","publication_year":2020,"publication_date":"2020-08-19","ids":{"openalex":"https://openalex.org/W3051352583","doi":"https://doi.org/10.1109/twc.2020.3016024","mag":"3051352583"},"language":"en","primary_location":{"id":"doi:10.1109/twc.2020.3016024","is_oa":false,"landing_page_url":"https://doi.org/10.1109/twc.2020.3016024","pdf_url":null,"source":{"id":"https://openalex.org/S63459445","display_name":"IEEE Transactions on Wireless Communications","issn_l":"1536-1276","issn":["1536-1276","1558-2248"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Transactions on Wireless Communications","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/A5007797149","display_name":"Ruijin Ding","orcid":"https://orcid.org/0000-0001-7441-3199"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ruijin Ding","raw_affiliation_strings":["Department of Automation, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China","Institute for Artificial Intelligence, Tsinghua University (THUAI), Beijing, China","State Key Laboratory of Intelligent Technologies and Systems, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-7441-3199","affiliations":[{"raw_affiliation_string":"Department of Automation, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Institute for Artificial Intelligence, Tsinghua University (THUAI), Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"State Key Laboratory of Intelligent Technologies and Systems, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050402661","display_name":"Feifei Gao","orcid":"https://orcid.org/0000-0001-8896-352X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feifei Gao","raw_affiliation_strings":["Department of Automation, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China","Institute for Artificial Intelligence, Tsinghua University (THUAI), Beijing, China","State Key Laboratory of Intelligent Technologies and Systems, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-8896-352X","affiliations":[{"raw_affiliation_string":"Department of Automation, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Institute for Artificial Intelligence, Tsinghua University (THUAI), Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"State Key Laboratory of Intelligent Technologies and Systems, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100773343","display_name":"Xuemin Shen","orcid":"https://orcid.org/0000-0002-4140-287X"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Xuemin Sherman Shen","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Canada"],"raw_orcid":"https://orcid.org/0000-0002-4140-287X","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Canada","institution_ids":["https://openalex.org/I151746483"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5007797149"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":267.0534,"has_fulltext":false,"cited_by_count":312,"citation_normalized_percentile":{"value":0.99989177,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"19","issue":"12","first_page":"7796","last_page":"7809"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11133","display_name":"UAV Applications and Optimization","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T11133","display_name":"UAV Applications and Optimization","score":1.0,"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"}},{"id":"https://openalex.org/T10249","display_name":"Distributed Control Multi-Agent Systems","score":0.9944000244140625,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9779999852180481,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.8314658999443054},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8004125952720642},{"id":"https://openalex.org/keywords/throughput","display_name":"Throughput","score":0.7909930944442749},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.7032376527786255},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.674316942691803},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.49354588985443115},{"id":"https://openalex.org/keywords/q-learning","display_name":"Q-learning","score":0.4881919026374817},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.4670400023460388},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.45994895696640015},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.38247162103652954},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.33988815546035767},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.31817784905433655},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.264864444732666},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.16790840029716492},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09861579537391663},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07462289929389954}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8314658999443054},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8004125952720642},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.7909930944442749},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.7032376527786255},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.674316942691803},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.49354588985443115},{"id":"https://openalex.org/C188116033","wikidata":"https://www.wikidata.org/wiki/Q2664563","display_name":"Q-learning","level":3,"score":0.4881919026374817},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.4670400023460388},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.45994895696640015},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.38247162103652954},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.33988815546035767},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.31817784905433655},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.264864444732666},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.16790840029716492},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09861579537391663},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07462289929389954},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","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/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/twc.2020.3016024","is_oa":false,"landing_page_url":"https://doi.org/10.1109/twc.2020.3016024","pdf_url":null,"source":{"id":"https://openalex.org/S63459445","display_name":"IEEE Transactions on Wireless Communications","issn_l":"1536-1276","issn":["1536-1276","1558-2248"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Transactions on Wireless Communications","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.9100000262260437}],"awards":[{"id":"https://openalex.org/G3762958806","display_name":null,"funder_award_id":"L182042","funder_id":"https://openalex.org/F4320322919","funder_display_name":"Natural Science Foundation of Beijing Municipality"},{"id":"https://openalex.org/G5896791982","display_name":null,"funder_award_id":"61771274","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8114187719","display_name":null,"funder_award_id":"61831013","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8616498718","display_name":null,"funder_award_id":"61531011","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G930939680","display_name":null,"funder_award_id":"4182030","funder_id":"https://openalex.org/F4320322919","funder_display_name":"Natural Science Foundation of Beijing Municipality"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322919","display_name":"Natural Science Foundation of Beijing Municipality","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W41554520","https://openalex.org/W1522301498","https://openalex.org/W1757796397","https://openalex.org/W1777239053","https://openalex.org/W1968594877","https://openalex.org/W1988456768","https://openalex.org/W2031834036","https://openalex.org/W2121863487","https://openalex.org/W2145339207","https://openalex.org/W2156737235","https://openalex.org/W2165150801","https://openalex.org/W2268751503","https://openalex.org/W2289204537","https://openalex.org/W2339958599","https://openalex.org/W2412503523","https://openalex.org/W2514674767","https://openalex.org/W2558431499","https://openalex.org/W2759529277","https://openalex.org/W2767105570","https://openalex.org/W2782363571","https://openalex.org/W2790256744","https://openalex.org/W2797086109","https://openalex.org/W2871357535","https://openalex.org/W2885293674","https://openalex.org/W2886509985","https://openalex.org/W2899898540","https://openalex.org/W2901790394","https://openalex.org/W2914952404","https://openalex.org/W2915369448","https://openalex.org/W2924948991","https://openalex.org/W2944127606","https://openalex.org/W2946763103","https://openalex.org/W2950373453","https://openalex.org/W2953948844","https://openalex.org/W2960647263","https://openalex.org/W2962751492","https://openalex.org/W2962804513","https://openalex.org/W2963569053","https://openalex.org/W2963615009","https://openalex.org/W2963864421","https://openalex.org/W2964023906","https://openalex.org/W2964121744","https://openalex.org/W3100862578","https://openalex.org/W3103377783","https://openalex.org/W4298857966","https://openalex.org/W4302570325","https://openalex.org/W6631190155","https://openalex.org/W6637967152","https://openalex.org/W6638088447","https://openalex.org/W6683195989","https://openalex.org/W6684205842","https://openalex.org/W6684921986"],"related_works":["https://openalex.org/W2742483371","https://openalex.org/W3096874164","https://openalex.org/W2166117066","https://openalex.org/W3087814763","https://openalex.org/W2357975469","https://openalex.org/W2136202932","https://openalex.org/W4376605461","https://openalex.org/W4400868993","https://openalex.org/W2361647908","https://openalex.org/W2952356279"],"abstract_inverted_index":{"Unmanned":[0],"Aerial":[1],"Vehicle":[2],"(UAV)-assisted":[3],"communication":[4,89,146],"has":[5],"drawn":[6],"increasing":[7],"attention":[8],"recently.":[9],"In":[10],"this":[11],"paper,":[12],"we":[13,38],"investigate":[14],"3D":[15,55],"UAV":[16,48,113],"trajectory":[17,91],"design":[18,92],"and":[19,29,62,71,93,120,129,138],"band":[20,94,142],"allocation":[21],"problem":[22],"considering":[23],"both":[24],"the":[25,30,33,41,53,60,63,66,98,112,117,126,131,134,157,163,165,171],"UAV's":[26,54],"energy":[27,42,127,135],"consumption":[28,43],"fairness":[31,61],"among":[32],"ground":[34],"users":[35],"(GUs).":[36],"Specifically,":[37],"first":[39],"formulate":[40],"model":[44],"of":[45,52,162],"a":[46,50,78],"quad-rotor":[47],"as":[49,85,107,123,168,170],"function":[51],"movement.":[56],"Then,":[57],"based":[58],"on":[59],"total":[64,166],"throughput,":[65,167],"fair":[67,88,145],"throughput":[68],"is":[69,136],"defined":[70],"maximized":[72],"within":[73],"limited":[74],"energy.":[75],"We":[76],"propose":[77],"deep":[79,102],"reinforcement":[80],"learning":[81],"(DRL)-based":[82],"algorithm,":[83,101],"named":[84],"EEFC-TDBA":[86,110,155],"(energy-efficient":[87],"through":[90],"allocation)":[95],"that":[96,154],"chooses":[97],"state-of-the-art":[99],"DRL":[100],"deterministic":[103],"policy":[104],"gradient":[105],"(DDPG),":[106],"its":[108],"basis.":[109],"allows":[111],"to:":[114],"1)":[115],"adjust":[116],"flight":[118],"speed":[119],"direction":[121],"so":[122],"to":[124,143,152],"enhance":[125],"efficiency":[128],"reach":[130],"destination":[132],"before":[133],"exhausted;":[137],"2)":[139],"allocate":[140],"frequency":[141],"achieve":[144],"service.":[147],"Simulation":[148],"results":[149],"are":[150],"provided":[151],"demonstrate":[153],"outperforms":[156],"baseline":[158],"methods":[159],"in":[160],"terms":[161],"fairness,":[164],"well":[169],"minimum":[172],"throughput.":[173]},"counts_by_year":[{"year":2026,"cited_by_count":9},{"year":2025,"cited_by_count":65},{"year":2024,"cited_by_count":72},{"year":2023,"cited_by_count":69},{"year":2022,"cited_by_count":57},{"year":2021,"cited_by_count":38},{"year":2019,"cited_by_count":2}],"updated_date":"2026-04-25T08:17:42.794288","created_date":"2025-10-10T00:00:00"}
