{"id":"https://openalex.org/W3006705564","doi":"https://doi.org/10.1109/globecom38437.2019.9014113","title":"Intelligent Beam Training for Millimeter-Wave Communications via Deep Reinforcement Learning","display_name":"Intelligent Beam Training for Millimeter-Wave Communications via Deep Reinforcement Learning","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W3006705564","doi":"https://doi.org/10.1109/globecom38437.2019.9014113","mag":"3006705564"},"language":"en","primary_location":{"id":"doi:10.1109/globecom38437.2019.9014113","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom38437.2019.9014113","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Global Communications Conference (GLOBECOM)","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/A5100358190","display_name":"Jianjun Zhang","orcid":"https://orcid.org/0000-0002-4830-1959"},"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"]},{"id":"https://openalex.org/I4210155350","display_name":"Purple Mountain Laboratories","ror":"https://ror.org/04zcbk583","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210155350"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jianjun Zhang","raw_affiliation_strings":["National Mobile Communications Research Laboratory, Southeast University, Nanjing, China","Purple Mountain Laboratories, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"National Mobile Communications Research Laboratory, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"Purple Mountain Laboratories, Nanjing, China","institution_ids":["https://openalex.org/I4210155350"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056225611","display_name":"Yongming Huang","orcid":"https://orcid.org/0009-0009-2545-2875"},"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"]},{"id":"https://openalex.org/I4210155350","display_name":"Purple Mountain Laboratories","ror":"https://ror.org/04zcbk583","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210155350"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongming Huang","raw_affiliation_strings":["National Mobile Communications Research Laboratory, Southeast University, Nanjing, China","Purple Mountain Laboratories, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"National Mobile Communications Research Laboratory, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"Purple Mountain Laboratories, Nanjing, China","institution_ids":["https://openalex.org/I4210155350"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085579919","display_name":"Jiaheng Wang","orcid":"https://orcid.org/0000-0002-9783-5471"},"institutions":[{"id":"https://openalex.org/I4210155350","display_name":"Purple Mountain Laboratories","ror":"https://ror.org/04zcbk583","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210155350"]},{"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":"Jiaheng Wang","raw_affiliation_strings":["National Mobile Communications Research Laboratory, Southeast University, Nanjing, China","Purple Mountain Laboratories, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"National Mobile Communications Research Laboratory, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"Purple Mountain Laboratories, Nanjing, China","institution_ids":["https://openalex.org/I4210155350"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072916702","display_name":"Xiaohu You","orcid":"https://orcid.org/0000-0002-0809-8511"},"institutions":[{"id":"https://openalex.org/I4210155350","display_name":"Purple Mountain Laboratories","ror":"https://ror.org/04zcbk583","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210155350"]},{"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":"Xiaohu You","raw_affiliation_strings":["National Mobile Communications Research Laboratory, Southeast University, Nanjing, China","Purple Mountain Laboratories, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"National Mobile Communications Research Laboratory, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"Purple Mountain Laboratories, Nanjing, China","institution_ids":["https://openalex.org/I4210155350"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100358190"],"corresponding_institution_ids":["https://openalex.org/I4210155350","https://openalex.org/I76569877"],"apc_list":null,"apc_paid":null,"fwci":1.4307,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.82833465,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10936","display_name":"Millimeter-Wave Propagation and Modeling","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10936","display_name":"Millimeter-Wave Propagation and Modeling","score":1.0,"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/T10262","display_name":"Microwave Engineering and Waveguides","score":0.9991000294685364,"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/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.9970999956130981,"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":0.7741921544075012},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.7683873176574707},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7470454573631287},{"id":"https://openalex.org/keywords/antenna","display_name":"Antenna (radio)","score":0.5359184741973877},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.5319004058837891},{"id":"https://openalex.org/keywords/extremely-high-frequency","display_name":"Extremely high frequency","score":0.5046669244766235},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.5021800994873047},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.4515881836414337},{"id":"https://openalex.org/keywords/beam","display_name":"Beam (structure)","score":0.4479503035545349},{"id":"https://openalex.org/keywords/train","display_name":"Train","score":0.43699905276298523},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.42027613520622253},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3049018383026123},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.23892733454704285},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.21166113018989563},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.15499064326286316}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7741921544075012},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.7683873176574707},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7470454573631287},{"id":"https://openalex.org/C21822782","wikidata":"https://www.wikidata.org/wiki/Q131214","display_name":"Antenna (radio)","level":2,"score":0.5359184741973877},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.5319004058837891},{"id":"https://openalex.org/C45764600","wikidata":"https://www.wikidata.org/wiki/Q570342","display_name":"Extremely high frequency","level":2,"score":0.5046669244766235},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5021800994873047},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4515881836414337},{"id":"https://openalex.org/C168834538","wikidata":"https://www.wikidata.org/wiki/Q3705329","display_name":"Beam (structure)","level":2,"score":0.4479503035545349},{"id":"https://openalex.org/C190839683","wikidata":"https://www.wikidata.org/wiki/Q2448197","display_name":"Train","level":2,"score":0.43699905276298523},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.42027613520622253},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3049018383026123},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.23892733454704285},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.21166113018989563},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.15499064326286316},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"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/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/globecom38437.2019.9014113","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom38437.2019.9014113","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Global Communications Conference (GLOBECOM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W41554520","https://openalex.org/W1956027752","https://openalex.org/W2053521124","https://openalex.org/W2121863487","https://openalex.org/W2145339207","https://openalex.org/W2173248099","https://openalex.org/W2198911682","https://openalex.org/W2259391824","https://openalex.org/W2261663070","https://openalex.org/W2314562768","https://openalex.org/W2604992528","https://openalex.org/W2614851539","https://openalex.org/W2615358882","https://openalex.org/W2725078910","https://openalex.org/W2737688805","https://openalex.org/W2748732524","https://openalex.org/W2805697023","https://openalex.org/W2897558090","https://openalex.org/W2962691384","https://openalex.org/W2963408914","https://openalex.org/W2963864421","https://openalex.org/W3099908750","https://openalex.org/W3102347753","https://openalex.org/W4289389607"],"related_works":["https://openalex.org/W618248309","https://openalex.org/W2377336366","https://openalex.org/W1568097102","https://openalex.org/W4390419160","https://openalex.org/W1601203902","https://openalex.org/W2075798043","https://openalex.org/W4225671779","https://openalex.org/W2102464536","https://openalex.org/W2361332776","https://openalex.org/W2248934910"],"abstract_inverted_index":{"Millimeter":[0],"wave":[1],"(mmwave)":[2],"communication":[3],"has":[4],"attracted":[5],"increasing":[6],"attention":[7],"owing":[8],"to":[9,25,45,130],"its":[10],"abundant":[11],"spectrum":[12],"resource.":[13],"The":[14,84],"short":[15],"wave-length":[16],"of":[17,37,65,91,122,133,143],"mmwave":[18],"signals":[19],"facilitates":[20],"exploiting":[21],"large":[22,27,32,38,47],"antenna":[23,39],"arrays":[24,40],"achieve":[26],"array":[28],"gains":[29],"and":[30,41,94,103,126,141],"combat":[31],"path-loss.":[33],"However,":[34],"the":[35,63,89,92,101,113,139,144],"use":[36],"narrow":[42],"beams":[43,106],"leads":[44],"a":[46,108,131],"overhead":[48,64],"in":[49,58,68],"beam":[50,66,77,147],"training":[51,78,148],"for":[52],"obtaining":[53],"channel":[54,124],"state":[55],"information,":[56],"especially":[57],"dynamic":[59,123],"environments.":[60],"To":[61],"reduce":[62],"training,":[67],"this":[69],"paper":[70],"we":[71],"propose":[72],"an":[73],"environment":[74,93],"sensing":[75],"based":[76],"algorithm":[79,86,115],"via":[80],"deep":[81],"reinforcement":[82],"learning.":[83],"proposed":[85,114,145],"can":[87],"sense":[88],"change":[90],"learn":[95],"required":[96],"latent":[97],"probability":[98],"information":[99],"from":[100],"environment,":[102],"intelligently":[104],"trains":[105],"with":[107],"low":[109],"overhead.":[110],"In":[111],"addition,":[112],"does":[116],"not":[117],"require":[118],"any":[119],"priori":[120],"knowledge":[121],"modeling,":[125],"thus":[127],"is":[128],"applicable":[129],"variety":[132],"complicated":[134],"scenarios.":[135],"Simulation":[136],"results":[137],"demonstrate":[138],"effectiveness":[140],"superiority":[142],"intelligent":[146],"algorithm.":[149]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
