{"id":"https://openalex.org/W7139079617","doi":"https://doi.org/10.1109/globecom59602.2025.11432705","title":"Prompt-guided Semantic Communication for Image Transmission with Dynamic Compression","display_name":"Prompt-guided Semantic Communication for Image Transmission with Dynamic Compression","publication_year":2025,"publication_date":"2025-12-08","ids":{"openalex":"https://openalex.org/W7139079617","doi":"https://doi.org/10.1109/globecom59602.2025.11432705"},"language":null,"primary_location":{"id":"doi:10.1109/globecom59602.2025.11432705","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom59602.2025.11432705","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2025 - 2025 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/A5130157006","display_name":"Peng Yi","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Peng Yi","raw_affiliation_strings":["University of Electronic Science and Technology of China (UESTC),Chengdu,P. R. China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China (UESTC),Chengdu,P. R. China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130076495","display_name":"Yang Cao","orcid":null},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Cao","raw_affiliation_strings":["Southwest Jiaotong University,Chengdu,P. R. China"],"affiliations":[{"raw_affiliation_string":"Southwest Jiaotong University,Chengdu,P. R. China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007832415","display_name":"Ying\u2010Chang Liang","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying-Chang Liang","raw_affiliation_strings":["University of Electronic Science and Technology of China (UESTC),Chengdu,P. R. China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China (UESTC),Chengdu,P. R. China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5130157006"],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.8674348,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3654","last_page":"3659"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.6341999769210815,"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"}},"topics":[{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.6341999769210815,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.047600001096725464,"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/T13918","display_name":"Advanced Data and IoT Technologies","score":0.04540000110864639,"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":0.609499990940094},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.5609999895095825},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5080000162124634},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.48019999265670776},{"id":"https://openalex.org/keywords/image-compression","display_name":"Image compression","score":0.4551999866962433},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.44690001010894775},{"id":"https://openalex.org/keywords/transmission","display_name":"Transmission (telecommunications)","score":0.38580000400543213},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.38179999589920044},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.36250001192092896}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8622999787330627},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.609499990940094},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.5609999895095825},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.527999997138977},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5080000162124634},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.48019999265670776},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.4551999866962433},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.44690001010894775},{"id":"https://openalex.org/C761482","wikidata":"https://www.wikidata.org/wiki/Q118093","display_name":"Transmission (telecommunications)","level":2,"score":0.38580000400543213},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.38179999589920044},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.36250001192092896},{"id":"https://openalex.org/C108037233","wikidata":"https://www.wikidata.org/wiki/Q11375","display_name":"Wireless network","level":3,"score":0.3578999936580658},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34599998593330383},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.34209999442100525},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3391000032424927},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.33709999918937683},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.32350000739097595},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3221000134944916},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.31869998574256897},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.3156000077724457},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.3124000132083893},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.301800012588501},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.29440000653266907},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.29159998893737793},{"id":"https://openalex.org/C37404715","wikidata":"https://www.wikidata.org/wiki/Q380679","display_name":"Dynamic programming","level":2,"score":0.2883000075817108},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.2745000123977661},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.27160000801086426},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.26910001039505005},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.26420000195503235},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.26409998536109924},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.25589999556541443},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.25529998540878296}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/globecom59602.2025.11432705","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom59602.2025.11432705","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2025 - 2025 IEEE Global Communications Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1861492603","https://openalex.org/W2974084046","https://openalex.org/W3113050802","https://openalex.org/W3155305558","https://openalex.org/W4313350220","https://openalex.org/W4388739236","https://openalex.org/W4390828922","https://openalex.org/W4391677749","https://openalex.org/W4392175488","https://openalex.org/W4401871087","https://openalex.org/W4402830956","https://openalex.org/W4413179339","https://openalex.org/W4414281281"],"related_works":[],"abstract_inverted_index":{"Semantic":[0,23],"communication":[1,189],"(SemCom)":[2],"has":[3],"emerged":[4],"as":[5],"a":[6,37,72,90],"key":[7,69],"paradigm":[8],"for":[9,141],"next-generation":[10],"wireless":[11],"networks.":[12],"However,":[13],"existing":[14],"SemCom":[15,40],"systems":[16],"face":[17],"challenges":[18],"in":[19,145],"adapting":[20],"to":[21,47,182],"dynamic":[22],"Entities":[24],"of":[25,92,148,157,173,196],"Interest":[26],"(SEI)":[27],"and":[28,60,126,136,151,166,177,193],"suffer":[29],"from":[30],"significant":[31],"computational":[32,109],"overhead.":[33,88],"This":[34],"paper":[35],"proposes":[36],"novel":[38],"Prompt-guided":[39],"(PSC)":[41],"framework":[42],"that":[43],"leverages":[44],"textual":[45,82],"prompts":[46],"dynamically":[48,76],"align":[49],"transmitted":[50],"image":[51,78],"features":[52,106],"with":[53,99],"the":[54,86,115,142,146,155,171,174,194],"receiver\u2019s":[55],"SEI,":[56],"enabling":[57,180],"adaptive":[58],"compression":[59],"enhanced":[61,163],"generalization.":[62],"The":[63],"proposed":[64],"PSC":[65,116,158,181],"system":[66],"introduces":[67],"two":[68],"features.":[70],"Specifically,":[71],"cross-modal":[73],"policy":[74,175],"network":[75,176],"selects":[77],"tokens":[79],"based":[80],"on":[81],"prompts,":[83],"thereby":[84],"minimizing":[85],"transmission":[87],"Moreover,":[89],"Mixture":[91],"Experts":[93],"(MoE)":[94],"architecture":[95],"enables":[96],"parallel":[97],"processing":[98],"sparse":[100],"expert":[101],"activation,":[102],"efficiently":[103],"handling":[104],"heterogeneous":[105],"while":[107,187],"reducing":[108,188],"complexity":[110],"during":[111],"inference.":[112],"To":[113],"train":[114],"system,":[117],"we":[118],"introduce":[119],"an":[120],"iterative":[121],"algorithm":[122],"combining":[123],"self-supervised":[124],"learning":[125],"Group":[127],"Relative":[128],"Policy":[129],"Optimization":[130],"(GRPO),":[131],"unifying":[132],"Deep":[133,137],"Learning":[134,139],"(DL)":[135],"Reinforcement":[138],"(DRL)":[140],"first":[143],"time":[144],"context":[147],"SEI":[149],"extraction":[150],"selection.":[152],"Experiments":[153],"demonstrate":[154],"superiority":[156],"over":[159],"conventional":[160],"methods,":[161],"achieving":[162],"reconstruction":[164,185],"performance":[165,186],"robustness.":[167],"Furthermore,":[168],"results":[169],"validate":[170],"effectiveness":[172],"MoE":[178],"architecture,":[179],"achieve":[183],"94.80%":[184],"overhead":[190],"by":[191,199],"44.90%":[192],"number":[195],"activated":[197],"parameters":[198],"47.04%.":[200]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2026-03-20T00:00:00"}