{"id":"https://openalex.org/W4315629699","doi":"https://doi.org/10.1109/globecom48099.2022.10000686","title":"Optimization of Image Transmission in Semantic Communication Networks","display_name":"Optimization of Image Transmission in Semantic Communication Networks","publication_year":2022,"publication_date":"2022-12-04","ids":{"openalex":"https://openalex.org/W4315629699","doi":"https://doi.org/10.1109/globecom48099.2022.10000686"},"language":"en","primary_location":{"id":"doi:10.1109/globecom48099.2022.10000686","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom48099.2022.10000686","pdf_url":null,"source":{"id":"https://openalex.org/S4363607705","display_name":"GLOBECOM 2022 - 2022 IEEE Global Communications Conference","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2022 - 2022 IEEE Global Communications Conference","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/A5004848485","display_name":"Wenjing Zhang","orcid":"https://orcid.org/0000-0002-2046-3948"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wenjing Zhang","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,Beijing Laboratory of Advanced Information Network,Beijing,China,100876"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,Beijing Laboratory of Advanced Information Network,Beijing,China,100876","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101796015","display_name":"Yining Wang","orcid":"https://orcid.org/0000-0003-2353-3400"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yining Wang","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,Beijing Laboratory of Advanced Information Network,Beijing,China,100876"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,Beijing Laboratory of Advanced Information Network,Beijing,China,100876","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072241033","display_name":"Mingzhe Chen","orcid":"https://orcid.org/0000-0003-2570-703X"},"institutions":[{"id":"https://openalex.org/I145608581","display_name":"University of Miami","ror":"https://ror.org/02dgjyy92","country_code":"US","type":"education","lineage":["https://openalex.org/I145608581"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mingzhe Chen","raw_affiliation_strings":["Institute for Data Science and Computing,University of Miami,Department of Electrical and Computer Engineering,Coral Gables,FL,USA,33146"],"affiliations":[{"raw_affiliation_string":"Institute for Data Science and Computing,University of Miami,Department of Electrical and Computer Engineering,Coral Gables,FL,USA,33146","institution_ids":["https://openalex.org/I145608581"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002713029","display_name":"Tao Luo","orcid":"https://orcid.org/0000-0003-4870-5942"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Luo","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,Beijing Laboratory of Advanced Information Network,Beijing,China,100876"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,Beijing Laboratory of Advanced Information Network,Beijing,China,100876","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091266202","display_name":"Dusit Niyato","orcid":"https://orcid.org/0000-0002-7442-7416"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Dusit Niyato","raw_affiliation_strings":["Nanyang Technological University,School of Computer Science and Engineering,Singapore","School of Computer Science and Engineering, Nanyang Technological University, Singapore"],"affiliations":[{"raw_affiliation_string":"Nanyang Technological University,School of Computer Science and Engineering,Singapore","institution_ids":["https://openalex.org/I172675005"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5004848485"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.5384,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.75833925,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"5965","last_page":"5970"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9944999814033508,"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"}},"topics":[{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9944999814033508,"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"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9918000102043152,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9839000105857849,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8280072212219238},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5243551731109619},{"id":"https://openalex.org/keywords/transmission","display_name":"Transmission (telecommunications)","score":0.4731146991252899},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.4698188602924347},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.4496229588985443},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.41727519035339355},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4019397497177124},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2518208622932434}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8280072212219238},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5243551731109619},{"id":"https://openalex.org/C761482","wikidata":"https://www.wikidata.org/wiki/Q118093","display_name":"Transmission (telecommunications)","level":2,"score":0.4731146991252899},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.4698188602924347},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.4496229588985443},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.41727519035339355},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4019397497177124},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2518208622932434},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/globecom48099.2022.10000686","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom48099.2022.10000686","pdf_url":null,"source":{"id":"https://openalex.org/S4363607705","display_name":"GLOBECOM 2022 - 2022 IEEE Global Communications Conference","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2022 - 2022 IEEE Global Communications Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Decent work and economic growth","score":0.41999998688697815,"id":"https://metadata.un.org/sdg/8"}],"awards":[{"id":"https://openalex.org/G2015320000","display_name":null,"funder_award_id":"62171047","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"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2019370496","https://openalex.org/W2133665775","https://openalex.org/W2155968351","https://openalex.org/W2277195237","https://openalex.org/W2746553466","https://openalex.org/W2781726626","https://openalex.org/W3035017890","https://openalex.org/W3036851434","https://openalex.org/W3090615085","https://openalex.org/W3134818623","https://openalex.org/W3135367836","https://openalex.org/W3139281747","https://openalex.org/W3156841666","https://openalex.org/W3166396011","https://openalex.org/W3166791908","https://openalex.org/W3198139956","https://openalex.org/W3203789000","https://openalex.org/W4206175303","https://openalex.org/W4210680217","https://openalex.org/W4285742007"],"related_works":["https://openalex.org/W4306904969","https://openalex.org/W2138720691","https://openalex.org/W4362501864","https://openalex.org/W4380318855","https://openalex.org/W3084456289","https://openalex.org/W2024136090","https://openalex.org/W4391331176","https://openalex.org/W2031695474","https://openalex.org/W2586732548","https://openalex.org/W2964765435"],"abstract_inverted_index":{"In":[0,12],"this":[1,70,121,143],"paper,":[2],"a":[3,15,21,59,147,168],"semantic":[4,26,37,54,64,84,104,116],"communication":[5,27,55],"framework":[6],"for":[7,115],"image":[8,18],"transmission":[9,134,196],"is":[10,73,129],"investigated.":[11],"the":[13,31,36,42,49,52,78,81,87,92,98,103,110,132,138,163,174,179,190,195,202,211],"framework,":[14],"server":[16,32,99],"transmits":[17],"data":[19],"to":[20,33,106,130,157,172,207,210],"set":[22],"of":[23,44,51,69,80,95,181],"users":[24],"utilizing":[25],"techniques,":[28],"which":[29],"enable":[30],"transmit":[34],"only":[35],"information":[38,85,105,117],"that":[39,74,189],"accurately":[40],"captures":[41],"meaning":[43,82],"an":[45,124,183],"image.":[46,89],"To":[47,90,141],"evaluate":[48],"performance":[50],"studied":[53],"system,":[56],"we":[57,145,166],"propose":[58,146],"multimodal":[60],"metric":[61,72],"called":[62],"image-to-graph":[63],"similarity":[65],"(ISS).":[66],"The":[67],"significance":[68],"new":[71],"it":[75],"can":[76,193],"measure":[77],"correlation":[79],"between":[83],"and":[86,109,200],"original":[88],"meet":[91],"ISS":[93,139],"requirement":[94],"each":[96],"user,":[97],"must":[100],"jointly":[101],"determine":[102],"be":[107],"transmitted":[108],"resource":[111],"blocks":[112],"(RBs)":[113],"used":[114],"transmission.":[118],"We":[119],"formulate":[120],"problem":[122,126],"as":[123],"optimization":[125],"whose":[127],"goal":[128],"minimize":[131],"average":[133],"latency":[135],"while":[136],"reaching":[137],"requirement.":[140],"solve":[142],"problem,":[144],"model-based":[148],"actor":[149,159,213],"critic":[150,160,214],"deep":[151],"reinforcement":[152],"learning":[153],"(DRL)":[154],"algorithm.":[155],"Compared":[156],"traditional":[158,212],"DRL,":[161],"in":[162],"proposed":[164,191],"algorithm,":[165],"design":[167],"novel":[169],"value":[170],"function":[171],"improve":[173],"action":[175],"exploration":[176],"thus":[177],"improving":[178],"probability":[180],"finding":[182],"optimal":[184],"solution.":[185],"Simulation":[186],"results":[187],"show":[188],"method":[192],"reduce":[194],"delay":[197],"by":[198,205],"16.4%":[199],"improves":[201],"convergence":[203],"speed":[204],"up":[206],"50%":[208],"compared":[209],"DRL.":[215]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}