{"id":"https://openalex.org/W4389989254","doi":"https://doi.org/10.1109/icnp59255.2023.10355575","title":"Rate-Distortion-Perception Theory for Semantic Communication","display_name":"Rate-Distortion-Perception Theory for Semantic Communication","publication_year":2023,"publication_date":"2023-10-10","ids":{"openalex":"https://openalex.org/W4389989254","doi":"https://doi.org/10.1109/icnp59255.2023.10355575"},"language":"en","primary_location":{"id":"doi:10.1109/icnp59255.2023.10355575","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icnp59255.2023.10355575","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 31st International Conference on Network Protocols (ICNP)","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/A5069758394","display_name":"Jingxuan Chai","orcid":"https://orcid.org/0000-0002-8633-5586"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jingxuan Chai","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University,Xi&#x0027;an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University,Xi&#x0027;an,China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100738543","display_name":"Yong Xiao","orcid":"https://orcid.org/0000-0002-4614-9017"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]},{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Xiao","raw_affiliation_strings":["School of Elect. Inform. &#x0026; Commun., Huazhong Univ. of Science &#x0026; Technology,China","Pazhou Laboratory (Huangpu), Guangzhou, China","Peng Cheng Laboratory, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Elect. Inform. &#x0026; Commun., Huazhong Univ. of Science &#x0026; Technology,China","institution_ids":["https://openalex.org/I47720641"]},{"raw_affiliation_string":"Pazhou Laboratory (Huangpu), Guangzhou, China","institution_ids":[]},{"raw_affiliation_string":"Peng Cheng Laboratory, Shenzhen, China","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101549504","display_name":"Guangming Shi","orcid":"https://orcid.org/0000-0003-2179-3292"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]},{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guangming Shi","raw_affiliation_strings":["Peng Cheng Laboratory,Shenzhen,China","Peng Cheng Laboratory, Shenzhen, China","Pazhou Laboratory (Huangpu), Guangzhou, China","School of Artificial Intelligence, Xidian University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peng Cheng Laboratory,Shenzhen,China","institution_ids":["https://openalex.org/I4210136793"]},{"raw_affiliation_string":"Peng Cheng Laboratory, Shenzhen, China","institution_ids":["https://openalex.org/I4210136793"]},{"raw_affiliation_string":"Pazhou Laboratory (Huangpu), Guangzhou, China","institution_ids":[]},{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024108653","display_name":"Walid Saad","orcid":"https://orcid.org/0000-0003-2247-2458"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Walid Saad","raw_affiliation_strings":["Virginia Tech,Bradley Department of Electrical and Computer Engineering,VA,USA","Bradley Department of Electrical and Computer Engineering, Virginia Tech, VA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Virginia Tech,Bradley Department of Electrical and Computer Engineering,VA,USA","institution_ids":["https://openalex.org/I859038795"]},{"raw_affiliation_string":"Bradley Department of Electrical and Computer Engineering, Virginia Tech, VA, USA","institution_ids":["https://openalex.org/I859038795"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5069758394"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":0.8878,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.746,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10964","display_name":"Wireless Communication Security Techniques","score":0.9998000264167786,"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/T10964","display_name":"Wireless Communication Security Techniques","score":0.9998000264167786,"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/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9947999715805054,"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/T11147","display_name":"Misinformation and Its Impacts","score":0.984499990940094,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7434403896331787},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6693840026855469},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.5446838736534119},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.5335165858268738},{"id":"https://openalex.org/keywords/rate\u2013distortion-theory","display_name":"Rate\u2013distortion theory","score":0.5063349008560181},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.4798550009727478},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.4514341950416565},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4356074929237366},{"id":"https://openalex.org/keywords/information-theory","display_name":"Information theory","score":0.4142621159553528},{"id":"https://openalex.org/keywords/semantic-integration","display_name":"Semantic integration","score":0.41264665126800537},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3601929545402527},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3480290472507477},{"id":"https://openalex.org/keywords/semantic-computing","display_name":"Semantic computing","score":0.3405207395553589},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14692795276641846},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.1386260986328125},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.09062248468399048},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08470037579536438}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7434403896331787},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6693840026855469},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.5446838736534119},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.5335165858268738},{"id":"https://openalex.org/C64185310","wikidata":"https://www.wikidata.org/wiki/Q843483","display_name":"Rate\u2013distortion theory","level":3,"score":0.5063349008560181},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.4798550009727478},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.4514341950416565},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4356074929237366},{"id":"https://openalex.org/C52622258","wikidata":"https://www.wikidata.org/wiki/Q131222","display_name":"Information theory","level":2,"score":0.4142621159553528},{"id":"https://openalex.org/C110903229","wikidata":"https://www.wikidata.org/wiki/Q7449064","display_name":"Semantic integration","level":4,"score":0.41264665126800537},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3601929545402527},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3480290472507477},{"id":"https://openalex.org/C511149849","wikidata":"https://www.wikidata.org/wiki/Q7449051","display_name":"Semantic computing","level":3,"score":0.3405207395553589},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14692795276641846},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.1386260986328125},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.09062248468399048},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08470037579536438},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C2129575","wikidata":"https://www.wikidata.org/wiki/Q54837","display_name":"Semantic Web","level":2,"score":0.0},{"id":"https://openalex.org/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"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/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icnp59255.2023.10355575","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icnp59255.2023.10355575","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 31st International Conference on Network Protocols (ICNP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.5899999737739563,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G1479125570","display_name":null,"funder_award_id":"62071193","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":19,"referenced_works":["https://openalex.org/W1995875735","https://openalex.org/W2126654067","https://openalex.org/W2133249991","https://openalex.org/W2768814045","https://openalex.org/W3098418424","https://openalex.org/W3197256000","https://openalex.org/W3198139956","https://openalex.org/W4226210362","https://openalex.org/W4289655294","https://openalex.org/W4310902984","https://openalex.org/W4312777148","https://openalex.org/W4313229659","https://openalex.org/W4386071976","https://openalex.org/W4386075103","https://openalex.org/W4386634577","https://openalex.org/W6758867260","https://openalex.org/W6790474340","https://openalex.org/W6795001324","https://openalex.org/W6810387544"],"related_works":["https://openalex.org/W3134365128","https://openalex.org/W2133831373","https://openalex.org/W2044128863","https://openalex.org/W2114077504","https://openalex.org/W1966422074","https://openalex.org/W2388928357","https://openalex.org/W2315308740","https://openalex.org/W2182534007","https://openalex.org/W1979325497","https://openalex.org/W2569612694"],"abstract_inverted_index":{"Semantic":[0],"communication":[1,21,77,143,220],"has":[2],"attracted":[3],"significant":[4],"interest":[5],"recently":[6],"due":[7],"to":[8,11,53,129,140,168,236],"its":[9],"capability":[10],"meet":[12],"the":[13,38,55,60,64,71,79,88,91,106,121,141,147,152,155,201,206,222,228],"fast":[14],"growing":[15],"demand":[16],"on":[17,45,227],"user-defined":[18],"and":[19,30,82,125,160,191,213],"human-oriented":[20],"services":[22],"such":[23],"as":[24],"holographic":[25],"communications,":[26],"eXtended":[27],"reality":[28],"(XR),":[29],"human-to-machine":[31],"interactions.":[32],"Unfortunately,":[33],"recent":[34],"study":[35,70],"suggests":[36],"that":[37,90,99,114,135,150,196,200],"traditional":[39],"Shannon":[40],"information":[41,93,112,134,185,208],"theory,":[42],"focusing":[43],"mainly":[44],"delivering":[46],"semantic-agnostic":[47],"symbols,":[48],"will":[49],"not":[50],"be":[51,102,117,137,169],"sufficient":[52],"investigate":[54],"semantic-level":[56],"perceptual":[57],"quality":[58],"of":[59,75,132],"recovered":[61],"messages":[62],"at":[63],"receiver.":[65],"In":[66],"this":[67],"paper,":[68],"we":[69,108],"achievable":[72,148,170,180],"data":[73,156,219],"rate":[74,181],"semantic":[76,83,92,111,161,184,207,230],"under":[78,187],"symbol":[80,158],"distortion":[81,190,212],"perception":[84,192,214],"constraints.":[85,193],"Motivated":[86],"by":[87,105,120,171],"fact":[89],"generally":[94],"involves":[95],"rich":[96],"intrinsic":[97],"knowledge":[98],"cannot":[100],"always":[101],"directly":[103,204],"observed":[104],"encoder,":[107],"consider":[109],"a":[110,172,178],"source":[113,186,209,231],"can":[115,127,203],"only":[116],"indirectly":[118],"sensed":[119],"encoder.":[122],"Both":[123],"encoder":[124],"decoder":[126],"access":[128],"various":[130],"types":[131],"side":[133],"may":[136],"closely":[138],"related":[139],"user's":[142],"preference.":[144],"We":[145,176,194],"derive":[146,177],"region":[149],"characterizes":[151],"tradeoff":[153],"among":[154],"rate,":[157],"distortion,":[159],"perception,":[162],"which":[163],"is":[164],"then":[165],"theoretically":[166],"proved":[167],"stochastic":[173],"coding":[174],"scheme.":[175],"closed-form":[179],"for":[182],"binary":[183],"any":[188,218],"given":[189],"observe":[195],"there":[197],"exists":[198],"cases":[199],"receiver":[202],"infer":[205],"satisfying":[210],"certain":[211],"constraints":[215],"without":[216],"requiring":[217],"from":[221],"transmitter.":[223],"Experimental":[224],"results":[225],"based":[226],"image":[229],"signal":[232],"have":[233],"been":[234],"presented":[235],"verify":[237],"our":[238],"theoretical":[239],"observations.":[240]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2}],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2025-10-10T00:00:00"}
