{"id":"https://openalex.org/W4408697779","doi":"https://doi.org/10.1109/twc.2025.3550266","title":"Energy-Efficient Multi-Agent Reinforcement Learning for UAV Trajectory Optimization in Cell-Free Massive MIMO Networks","display_name":"Energy-Efficient Multi-Agent Reinforcement Learning for UAV Trajectory Optimization in Cell-Free Massive MIMO Networks","publication_year":2025,"publication_date":"2025-03-21","ids":{"openalex":"https://openalex.org/W4408697779","doi":"https://doi.org/10.1109/twc.2025.3550266"},"language":"en","primary_location":{"id":"doi:10.1109/twc.2025.3550266","is_oa":false,"landing_page_url":"https://doi.org/10.1109/twc.2025.3550266","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/A5101405969","display_name":"Zhilong Liu","orcid":"https://orcid.org/0000-0002-0401-5010"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhilong Liu","raw_affiliation_strings":["State Key Laboratory of Advanced Rail Autonomous Operation, Beijing, China","Collaborative Innovation Center of Railway Traffic Safety, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0401-5010","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Advanced Rail Autonomous Operation, Beijing, China","institution_ids":[]},{"raw_affiliation_string":"Collaborative Innovation Center of Railway Traffic Safety, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100612301","display_name":"Jiayi Zhang","orcid":"https://orcid.org/0000-0003-2434-4329"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiayi Zhang","raw_affiliation_strings":["State Key Laboratory of Advanced Rail Autonomous Operation, Beijing, China","Collaborative Innovation Center of Railway Traffic Safety, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-2434-4329","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Advanced Rail Autonomous Operation, Beijing, China","institution_ids":[]},{"raw_affiliation_string":"Collaborative Innovation Center of Railway Traffic Safety, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082336235","display_name":"Yong Zeng","orcid":"https://orcid.org/0000-0002-3670-0434"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Zeng","raw_affiliation_strings":["National Mobile Communications Research Laboratory, Southeast University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-3670-0434","affiliations":[{"raw_affiliation_string":"National Mobile Communications Research Laboratory, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100620739","display_name":"Bo Ai","orcid":"https://orcid.org/0000-0001-6850-0595"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bo Ai","raw_affiliation_strings":["State Key Laboratory of Advanced Rail Autonomous Operation, Beijing, China","Collaborative Innovation Center of Railway Traffic Safety, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-6850-0595","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Advanced Rail Autonomous Operation, Beijing, China","institution_ids":[]},{"raw_affiliation_string":"Collaborative Innovation Center of Railway Traffic Safety, Beijing, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":35.9163,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.99606101,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"24","issue":"7","first_page":"5917","last_page":"5930"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11133","display_name":"UAV Applications and Optimization","score":0.9994000196456909,"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":0.9994000196456909,"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":0.9961000084877014,"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":0.9922999739646912,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.8282192945480347},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7060461640357971},{"id":"https://openalex.org/keywords/mimo","display_name":"MIMO","score":0.6867236495018005},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.6019194722175598},{"id":"https://openalex.org/keywords/trajectory-optimization","display_name":"Trajectory optimization","score":0.5385990738868713},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.4746970534324646},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4080224335193634},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.282227486371994},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.24785694479942322},{"id":"https://openalex.org/keywords/optimal-control","display_name":"Optimal control","score":0.14793547987937927},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12820672988891602},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09366908669471741}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8282192945480347},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7060461640357971},{"id":"https://openalex.org/C207987634","wikidata":"https://www.wikidata.org/wiki/Q176862","display_name":"MIMO","level":3,"score":0.6867236495018005},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.6019194722175598},{"id":"https://openalex.org/C173246807","wikidata":"https://www.wikidata.org/wiki/Q7833062","display_name":"Trajectory optimization","level":3,"score":0.5385990738868713},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.4746970534324646},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4080224335193634},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.282227486371994},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.24785694479942322},{"id":"https://openalex.org/C91575142","wikidata":"https://www.wikidata.org/wiki/Q1971426","display_name":"Optimal control","level":2,"score":0.14793547987937927},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12820672988891602},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09366908669471741},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"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.2025.3550266","is_oa":false,"landing_page_url":"https://doi.org/10.1109/twc.2025.3550266","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":0.8399999737739563}],"awards":[{"id":"https://openalex.org/G1785436436","display_name":null,"funder_award_id":"IA20240709018","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5331489779","display_name":null,"funder_award_id":"62221001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7052355602","display_name":null,"funder_award_id":"2022JBQY004","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G8663935928","display_name":null,"funder_award_id":"62471027","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W2268751503","https://openalex.org/W2962804513","https://openalex.org/W2964005248","https://openalex.org/W2969525674","https://openalex.org/W2974046131","https://openalex.org/W2994008524","https://openalex.org/W3004946548","https://openalex.org/W3034448035","https://openalex.org/W3044817033","https://openalex.org/W3048217314","https://openalex.org/W3080511272","https://openalex.org/W3110989801","https://openalex.org/W3132105662","https://openalex.org/W3161326013","https://openalex.org/W3169591209","https://openalex.org/W3181930796","https://openalex.org/W3217090259","https://openalex.org/W4205140704","https://openalex.org/W4225757433","https://openalex.org/W4289823361","https://openalex.org/W4292261130","https://openalex.org/W4293221718","https://openalex.org/W4297912121","https://openalex.org/W4298848549","https://openalex.org/W4312597125","https://openalex.org/W4376481253","https://openalex.org/W4377235318","https://openalex.org/W4384080812","https://openalex.org/W4384916959","https://openalex.org/W4387490149","https://openalex.org/W4387885634","https://openalex.org/W4389934310","https://openalex.org/W4390496060","https://openalex.org/W4391093003","https://openalex.org/W4391128868","https://openalex.org/W4392939679","https://openalex.org/W4400351173","https://openalex.org/W4401507748","https://openalex.org/W4402627639","https://openalex.org/W4403182025","https://openalex.org/W4404370900","https://openalex.org/W6857394249"],"related_works":["https://openalex.org/W4385832323","https://openalex.org/W4244391535","https://openalex.org/W2356996864","https://openalex.org/W2904060783","https://openalex.org/W2015393961","https://openalex.org/W2378339670","https://openalex.org/W2359353485","https://openalex.org/W2361427670","https://openalex.org/W2139910871","https://openalex.org/W2119925415"],"abstract_inverted_index":{"To":[0,47,132],"enhance":[1],"global":[2],"data":[3],"transmission,":[4],"uncrewed":[5],"aerial":[6],"vehicle":[7],"(UAV)-aided":[8],"space-air-ground":[9],"integrated":[10],"networks":[11],"(SAGIN)":[12],"represent":[13],"a":[14,53,107,146,152,167],"pivotal":[15],"direction":[16],"for":[17,94],"future":[18],"advancements.":[19],"In":[20,99,158],"this":[21,48],"paper,":[22],"we":[23,50,84,165],"focus":[24],"on":[25,112],"the":[26,31,35,41,72,86,95,103,126,134,162,172,178,186,197,203],"trajectory":[27,136],"optimization":[28,137,205],"problem":[29],"with":[30,44],"goal":[32],"of":[33,75,82,129],"maximizing":[34],"energy":[36,45],"efficiency":[37],"(EE),":[38],"thereby":[39],"balancing":[40],"system":[42],"capacity":[43],"expenditure.":[46],"end,":[49],"first":[51],"introduce":[52],"cell-free":[54],"SAGIN":[55],"network":[56,170],"where":[57],"UAVs":[58],"function":[59],"as":[60],"flying":[61],"access":[62,105],"points":[63],"to":[64,101,160,176],"serve":[65],"ground":[66],"user":[67],"equipment":[68],"(GUE).":[69],"Given":[70],"that":[71,81,196],"transmission":[73],"power":[74,127],"satellite":[76],"direct-to-cell":[77],"devices":[78],"typically":[79],"exceeds":[80],"GUEs,":[83],"investigate":[85],"interference":[87],"effect":[88],"and":[89,151,190,202],"derive":[90],"exact":[91],"closed-form":[92],"expressions":[93],"uplink":[96],"spectral":[97],"efficiency.":[98],"order":[100],"improve":[102],"service":[104],"efficiency,":[106],"GUE":[108,199],"grouping":[109,200],"scheme":[110],"based":[111],"density":[113],"distribution":[114],"is":[115,123],"proposed.":[116],"Then,":[117],"an":[118],"effective":[119],"EE":[120],"analysis":[121],"model":[122],"established":[124],"considering":[125],"consumption":[128],"fixed-wing":[130],"UAVs.":[131],"solve":[133],"UAV":[135,187],"problem,":[138],"two":[139,142],"algorithms":[140],"over":[141],"timescales":[143],"are":[144],"proposed:":[145],"successive":[147],"convex":[148],"approximation":[149],"strategy":[150],"multi-agent":[153],"reinforcement":[154],"learning":[155],"(MARL)-based":[156],"algorithm.":[157],"particular,":[159],"reduce":[161,177],"algorithmic":[163],"complexity,":[164],"employ":[166],"shared":[168],"Critic":[169],"in":[171,209],"proposed":[173,198],"MARL":[174],"algorithm":[175,201,206],"training":[179],"parameters.":[180,192],"Importantly,":[181],"our":[182],"approach":[183],"comprehensively":[184],"optimizes":[185],"trajectory,":[188],"acceleration,":[189],"velocity":[191],"The":[193],"results":[194],"show":[195],"MARL-based":[204],"demonstrate":[207],"adaptability":[208],"dynamic":[210],"time-varying":[211],"environments.":[212]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":8}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}