Extended Blahut–Arimoto Algorithm for Semantic Rate-Distortion Function Article Swipe
Yuxin Han
,
Yang Liu
,
Yaping Sun
,
Kai Niu
,
Nan Ma
,
Shuguang Cui
,
Ping Zhang
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/e27060651
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/e27060651
Semantic communication has recently gained significant attention in theoretical analysis due to its potential to improve communication efficiency by focusing on meaning rather than exact signal reconstruction. In this paper, we extend the Blahut–Arimoto (BA) algorithm, a fundamental method in classical information theory (CIT) for computing the rate-distortion (RD) function, to semantic communication by proposing the extended Blahut–Arimoto (EBA) algorithm, which iteratively updates transition and reconstruction distributions to calculate the semantic RD function based on synonymous mapping in semantic information theory (SIT). To address scenarios where synonymous mappings are unknown, we develop an optimization framework that combines the EBA algorithm with simulated annealing. Initialized with a syntactic mapping, the framework progressively merges syntactic symbols and identifies the mapping with a maximum synonymous number that satisfies objective constraints. Furthermore, by considering the semantic knowledge base (SKB) as a specific instance of synonymous mapping, the EBA algorithm provides a theoretical approach for analyzing and predicting the SKB size. Numerical results validate the effectiveness of the EBA algorithm. For Gaussian sources, the semantic RD function decreases with an increasing synonymous number and becomes significantly lower than its classical counterpart. Additionally, analysis on the CUB dataset demonstrates that larger SKB sizes lead to higher semantic communication compression efficiency.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/e27060651
- https://www.mdpi.com/1099-4300/27/6/651/pdf?version=1750245143
- OA Status
- gold
- Cited By
- 1
- References
- 30
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4411421902
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4411421902Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/e27060651Digital Object Identifier
- Title
-
Extended Blahut–Arimoto Algorithm for Semantic Rate-Distortion FunctionWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-06-18Full publication date if available
- Authors
-
Yuxin Han, Yang Liu, Yaping Sun, Kai Niu, Nan Ma, Shuguang Cui, Ping ZhangList of authors in order
- Landing page
-
https://doi.org/10.3390/e27060651Publisher landing page
- PDF URL
-
https://www.mdpi.com/1099-4300/27/6/651/pdf?version=1750245143Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/1099-4300/27/6/651/pdf?version=1750245143Direct OA link when available
- Concepts
-
Function (biology), Algorithm, Distortion (music), Computer science, Pattern recognition (psychology), Mathematics, Statistical physics, Physics, Artificial intelligence, Data mining, Biology, Computer network, Bandwidth (computing), Amplifier, Evolutionary biologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1Per-year citation counts (last 5 years)
- References (count)
-
30Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4411421902 |
|---|---|
| doi | https://doi.org/10.3390/e27060651 |
| ids.doi | https://doi.org/10.3390/e27060651 |
| ids.pmid | https://pubmed.ncbi.nlm.nih.gov/40566238 |
| ids.openalex | https://openalex.org/W4411421902 |
| fwci | 4.81974515 |
| type | article |
| title | Extended Blahut–Arimoto Algorithm for Semantic Rate-Distortion Function |
| awards[0].id | https://openalex.org/G4764165505 |
| awards[0].funder_id | https://openalex.org/F4320321001 |
| awards[0].display_name | |
| awards[0].funder_award_id | 62471054 |
| awards[0].funder_display_name | National Natural Science Foundation of China |
| awards[1].id | https://openalex.org/G3717553876 |
| awards[1].funder_id | https://openalex.org/F4320321001 |
| awards[1].display_name | |
| awards[1].funder_award_id | 9246730007 |
| awards[1].funder_display_name | National Natural Science Foundation of China |
| awards[2].id | https://openalex.org/G6454029087 |
| awards[2].funder_id | https://openalex.org/F4320321001 |
| awards[2].display_name | |
| awards[2].funder_award_id | 62293481 |
| awards[2].funder_display_name | National Natural Science Foundation of China |
| awards[3].id | https://openalex.org/G6352250275 |
| awards[3].funder_id | https://openalex.org/F4320321001 |
| awards[3].display_name | |
| awards[3].funder_award_id | 62293482 |
| awards[3].funder_display_name | National Natural Science Foundation of China |
| awards[4].id | https://openalex.org/G2002337963 |
| awards[4].funder_id | https://openalex.org/F4320321001 |
| awards[4].display_name | |
| awards[4].funder_award_id | 62301471 |
| awards[4].funder_display_name | National Natural Science Foundation of China |
| biblio.issue | 6 |
| biblio.volume | 27 |
| biblio.last_page | 651 |
| biblio.first_page | 651 |
| topics[0].id | https://openalex.org/T12131 |
| topics[0].field.id | https://openalex.org/fields/17 |
| topics[0].field.display_name | Computer Science |
| topics[0].score | 0.9998999834060669 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1702 |
| topics[0].subfield.display_name | Artificial Intelligence |
| topics[0].display_name | Wireless Signal Modulation Classification |
| topics[1].id | https://openalex.org/T10891 |
| topics[1].field.id | https://openalex.org/fields/22 |
| topics[1].field.display_name | Engineering |
| topics[1].score | 0.9991999864578247 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2202 |
| topics[1].subfield.display_name | Aerospace Engineering |
| topics[1].display_name | Radar Systems and Signal Processing |
| topics[2].id | https://openalex.org/T11447 |
| topics[2].field.id | https://openalex.org/fields/17 |
| topics[2].field.display_name | Computer Science |
| topics[2].score | 0.9987000226974487 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/1711 |
| topics[2].subfield.display_name | Signal Processing |
| topics[2].display_name | Blind Source Separation Techniques |
| funders[0].id | https://openalex.org/F4320321001 |
| funders[0].ror | https://ror.org/01h0zpd94 |
| funders[0].display_name | National Natural Science Foundation of China |
| is_xpac | False |
| apc_list.value | 2000 |
| apc_list.currency | CHF |
| apc_list.value_usd | 2165 |
| apc_paid.value | 2000 |
| apc_paid.currency | CHF |
| apc_paid.value_usd | 2165 |
| concepts[0].id | https://openalex.org/C14036430 |
| concepts[0].level | 2 |
| concepts[0].score | 0.5315850377082825 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q3736076 |
| concepts[0].display_name | Function (biology) |
| concepts[1].id | https://openalex.org/C11413529 |
| concepts[1].level | 1 |
| concepts[1].score | 0.5104100108146667 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q8366 |
| concepts[1].display_name | Algorithm |
| concepts[2].id | https://openalex.org/C126780896 |
| concepts[2].level | 4 |
| concepts[2].score | 0.4569163918495178 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q899871 |
| concepts[2].display_name | Distortion (music) |
| concepts[3].id | https://openalex.org/C41008148 |
| concepts[3].level | 0 |
| concepts[3].score | 0.4538570046424866 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[3].display_name | Computer science |
| concepts[4].id | https://openalex.org/C153180895 |
| concepts[4].level | 2 |
| concepts[4].score | 0.4001050591468811 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q7148389 |
| concepts[4].display_name | Pattern recognition (psychology) |
| concepts[5].id | https://openalex.org/C33923547 |
| concepts[5].level | 0 |
| concepts[5].score | 0.39840394258499146 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[5].display_name | Mathematics |
| concepts[6].id | https://openalex.org/C121864883 |
| concepts[6].level | 1 |
| concepts[6].score | 0.3896941840648651 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q677916 |
| concepts[6].display_name | Statistical physics |
| concepts[7].id | https://openalex.org/C121332964 |
| concepts[7].level | 0 |
| concepts[7].score | 0.36788880825042725 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q413 |
| concepts[7].display_name | Physics |
| concepts[8].id | https://openalex.org/C154945302 |
| concepts[8].level | 1 |
| concepts[8].score | 0.35385048389434814 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[8].display_name | Artificial intelligence |
| concepts[9].id | https://openalex.org/C124101348 |
| concepts[9].level | 1 |
| concepts[9].score | 0.3274458646774292 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q172491 |
| concepts[9].display_name | Data mining |
| concepts[10].id | https://openalex.org/C86803240 |
| concepts[10].level | 0 |
| concepts[10].score | 0.08862194418907166 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q420 |
| concepts[10].display_name | Biology |
| concepts[11].id | https://openalex.org/C31258907 |
| concepts[11].level | 1 |
| concepts[11].score | 0.0 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q1301371 |
| concepts[11].display_name | Computer network |
| concepts[12].id | https://openalex.org/C2776257435 |
| concepts[12].level | 2 |
| concepts[12].score | 0.0 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q1576430 |
| concepts[12].display_name | Bandwidth (computing) |
| concepts[13].id | https://openalex.org/C194257627 |
| concepts[13].level | 3 |
| concepts[13].score | 0.0 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q211554 |
| concepts[13].display_name | Amplifier |
| concepts[14].id | https://openalex.org/C78458016 |
| concepts[14].level | 1 |
| concepts[14].score | 0.0 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q840400 |
| concepts[14].display_name | Evolutionary biology |
| keywords[0].id | https://openalex.org/keywords/function |
| keywords[0].score | 0.5315850377082825 |
| keywords[0].display_name | Function (biology) |
| keywords[1].id | https://openalex.org/keywords/algorithm |
| keywords[1].score | 0.5104100108146667 |
| keywords[1].display_name | Algorithm |
| keywords[2].id | https://openalex.org/keywords/distortion |
| keywords[2].score | 0.4569163918495178 |
| keywords[2].display_name | Distortion (music) |
| keywords[3].id | https://openalex.org/keywords/computer-science |
| keywords[3].score | 0.4538570046424866 |
| keywords[3].display_name | Computer science |
| keywords[4].id | https://openalex.org/keywords/pattern-recognition |
| keywords[4].score | 0.4001050591468811 |
| keywords[4].display_name | Pattern recognition (psychology) |
| keywords[5].id | https://openalex.org/keywords/mathematics |
| keywords[5].score | 0.39840394258499146 |
| keywords[5].display_name | Mathematics |
| keywords[6].id | https://openalex.org/keywords/statistical-physics |
| keywords[6].score | 0.3896941840648651 |
| keywords[6].display_name | Statistical physics |
| keywords[7].id | https://openalex.org/keywords/physics |
| keywords[7].score | 0.36788880825042725 |
| keywords[7].display_name | Physics |
| keywords[8].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[8].score | 0.35385048389434814 |
| keywords[8].display_name | Artificial intelligence |
| keywords[9].id | https://openalex.org/keywords/data-mining |
| keywords[9].score | 0.3274458646774292 |
| keywords[9].display_name | Data mining |
| keywords[10].id | https://openalex.org/keywords/biology |
| keywords[10].score | 0.08862194418907166 |
| keywords[10].display_name | Biology |
| language | en |
| locations[0].id | doi:10.3390/e27060651 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S195231649 |
| locations[0].source.issn | 1099-4300 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 1099-4300 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | Entropy |
| locations[0].source.host_organization | https://openalex.org/P4310310987 |
| locations[0].source.host_organization_name | Multidisciplinary Digital Publishing Institute |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310310987 |
| locations[0].source.host_organization_lineage_names | Multidisciplinary Digital Publishing Institute |
| locations[0].license | cc-by |
| locations[0].pdf_url | https://www.mdpi.com/1099-4300/27/6/651/pdf?version=1750245143 |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Entropy |
| locations[0].landing_page_url | https://doi.org/10.3390/e27060651 |
| locations[1].id | pmid:40566238 |
| locations[1].is_oa | False |
| locations[1].source.id | https://openalex.org/S4306525036 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | PubMed |
| locations[1].source.host_organization | https://openalex.org/I1299303238 |
| locations[1].source.host_organization_name | National Institutes of Health |
| locations[1].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | publishedVersion |
| locations[1].raw_type | |
| locations[1].license_id | |
| locations[1].is_accepted | True |
| locations[1].is_published | True |
| locations[1].raw_source_name | Entropy (Basel, Switzerland) |
| locations[1].landing_page_url | https://pubmed.ncbi.nlm.nih.gov/40566238 |
| locations[2].id | pmh:oai:doaj.org/article:2426b95d4a3845aba0864cc68b545129 |
| locations[2].is_oa | False |
| locations[2].source.id | https://openalex.org/S4306401280 |
| locations[2].source.issn | |
| locations[2].source.type | repository |
| locations[2].source.is_oa | False |
| locations[2].source.issn_l | |
| locations[2].source.is_core | False |
| locations[2].source.is_in_doaj | False |
| locations[2].source.display_name | DOAJ (DOAJ: Directory of Open Access Journals) |
| locations[2].source.host_organization | |
| locations[2].source.host_organization_name | |
| locations[2].license | |
| locations[2].pdf_url | |
| locations[2].version | submittedVersion |
| locations[2].raw_type | article |
| locations[2].license_id | |
| locations[2].is_accepted | False |
| locations[2].is_published | False |
| locations[2].raw_source_name | Entropy, Vol 27, Iss 6, p 651 (2025) |
| locations[2].landing_page_url | https://doaj.org/article/2426b95d4a3845aba0864cc68b545129 |
| locations[3].id | pmh:oai:pubmedcentral.nih.gov:12192163 |
| locations[3].is_oa | True |
| locations[3].source.id | https://openalex.org/S2764455111 |
| locations[3].source.issn | |
| locations[3].source.type | repository |
| locations[3].source.is_oa | False |
| locations[3].source.issn_l | |
| locations[3].source.is_core | False |
| locations[3].source.is_in_doaj | False |
| locations[3].source.display_name | PubMed Central |
| locations[3].source.host_organization | https://openalex.org/I1299303238 |
| locations[3].source.host_organization_name | National Institutes of Health |
| locations[3].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[3].license | other-oa |
| locations[3].pdf_url | |
| locations[3].version | submittedVersion |
| locations[3].raw_type | Text |
| locations[3].license_id | https://openalex.org/licenses/other-oa |
| locations[3].is_accepted | False |
| locations[3].is_published | False |
| locations[3].raw_source_name | Entropy (Basel) |
| locations[3].landing_page_url | https://www.ncbi.nlm.nih.gov/pmc/articles/12192163 |
| indexed_in | crossref, doaj, pubmed |
| authorships[0].author.id | https://openalex.org/A5048804171 |
| authorships[0].author.orcid | https://orcid.org/0009-0001-1665-0767 |
| authorships[0].author.display_name | Yuxin Han |
| authorships[0].countries | CN |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I139759216 |
| authorships[0].affiliations[0].raw_affiliation_string | Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing 100876, China |
| authorships[0].affiliations[1].institution_ids | https://openalex.org/I4210136793 |
| authorships[0].affiliations[1].raw_affiliation_string | Department of Broadband Communication, Pengcheng Laboratory, Shenzhen 518055, China |
| authorships[0].institutions[0].id | https://openalex.org/I139759216 |
| authorships[0].institutions[0].ror | https://ror.org/04w9fbh59 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I139759216 |
| authorships[0].institutions[0].country_code | CN |
| authorships[0].institutions[0].display_name | Beijing University of Posts and Telecommunications |
| authorships[0].institutions[1].id | https://openalex.org/I4210136793 |
| authorships[0].institutions[1].ror | https://ror.org/03qdqbt06 |
| authorships[0].institutions[1].type | facility |
| authorships[0].institutions[1].lineage | https://openalex.org/I4210136793 |
| authorships[0].institutions[1].country_code | CN |
| authorships[0].institutions[1].display_name | Peng Cheng Laboratory |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Yuxin Han |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Department of Broadband Communication, Pengcheng Laboratory, Shenzhen 518055, China, Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing 100876, China |
| authorships[1].author.id | https://openalex.org/A5100654081 |
| authorships[1].author.orcid | https://orcid.org/0000-0001-9814-638X |
| authorships[1].author.display_name | Yang Liu |
| authorships[1].countries | CN |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I4210136793 |
| authorships[1].affiliations[0].raw_affiliation_string | Department of Broadband Communication, Pengcheng Laboratory, Shenzhen 518055, China |
| authorships[1].affiliations[1].institution_ids | https://openalex.org/I139759216 |
| authorships[1].affiliations[1].raw_affiliation_string | Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing 100876, China |
| authorships[1].institutions[0].id | https://openalex.org/I139759216 |
| authorships[1].institutions[0].ror | https://ror.org/04w9fbh59 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I139759216 |
| authorships[1].institutions[0].country_code | CN |
| authorships[1].institutions[0].display_name | Beijing University of Posts and Telecommunications |
| authorships[1].institutions[1].id | https://openalex.org/I4210136793 |
| authorships[1].institutions[1].ror | https://ror.org/03qdqbt06 |
| authorships[1].institutions[1].type | facility |
| authorships[1].institutions[1].lineage | https://openalex.org/I4210136793 |
| authorships[1].institutions[1].country_code | CN |
| authorships[1].institutions[1].display_name | Peng Cheng Laboratory |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Yang Liu |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Department of Broadband Communication, Pengcheng Laboratory, Shenzhen 518055, China, Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing 100876, China |
| authorships[2].author.id | https://openalex.org/A5102508017 |
| authorships[2].author.orcid | |
| authorships[2].author.display_name | Yaping Sun |
| authorships[2].countries | CN |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I4210136793 |
| authorships[2].affiliations[0].raw_affiliation_string | Department of Broadband Communication, Pengcheng Laboratory, Shenzhen 518055, China |
| authorships[2].affiliations[1].institution_ids | https://openalex.org/I4210116924 |
| authorships[2].affiliations[1].raw_affiliation_string | School of Science and Engineering (SSE) and the Future Network of Intelligent Institute (FNii), The Chinese University of Hong Kong (Shenzhen), Shenzhen 518172, China |
| authorships[2].institutions[0].id | https://openalex.org/I4210116924 |
| authorships[2].institutions[0].ror | https://ror.org/02d5ks197 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I177725633, https://openalex.org/I180726961, https://openalex.org/I4210116924 |
| authorships[2].institutions[0].country_code | CN |
| authorships[2].institutions[0].display_name | Chinese University of Hong Kong, Shenzhen |
| authorships[2].institutions[1].id | https://openalex.org/I4210136793 |
| authorships[2].institutions[1].ror | https://ror.org/03qdqbt06 |
| authorships[2].institutions[1].type | facility |
| authorships[2].institutions[1].lineage | https://openalex.org/I4210136793 |
| authorships[2].institutions[1].country_code | CN |
| authorships[2].institutions[1].display_name | Peng Cheng Laboratory |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Yaping Sun |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Department of Broadband Communication, Pengcheng Laboratory, Shenzhen 518055, China, School of Science and Engineering (SSE) and the Future Network of Intelligent Institute (FNii), The Chinese University of Hong Kong (Shenzhen), Shenzhen 518172, China |
| authorships[3].author.id | https://openalex.org/A5008455605 |
| authorships[3].author.orcid | https://orcid.org/0000-0002-8076-1867 |
| authorships[3].author.display_name | Kai Niu |
| authorships[3].countries | CN |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I4210136793 |
| authorships[3].affiliations[0].raw_affiliation_string | Department of Broadband Communication, Pengcheng Laboratory, Shenzhen 518055, China |
| authorships[3].affiliations[1].institution_ids | https://openalex.org/I139759216 |
| authorships[3].affiliations[1].raw_affiliation_string | Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing 100876, China |
| authorships[3].institutions[0].id | https://openalex.org/I139759216 |
| authorships[3].institutions[0].ror | https://ror.org/04w9fbh59 |
| authorships[3].institutions[0].type | education |
| authorships[3].institutions[0].lineage | https://openalex.org/I139759216 |
| authorships[3].institutions[0].country_code | CN |
| authorships[3].institutions[0].display_name | Beijing University of Posts and Telecommunications |
| authorships[3].institutions[1].id | https://openalex.org/I4210136793 |
| authorships[3].institutions[1].ror | https://ror.org/03qdqbt06 |
| authorships[3].institutions[1].type | facility |
| authorships[3].institutions[1].lineage | https://openalex.org/I4210136793 |
| authorships[3].institutions[1].country_code | CN |
| authorships[3].institutions[1].display_name | Peng Cheng Laboratory |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Kai Niu |
| authorships[3].is_corresponding | True |
| authorships[3].raw_affiliation_strings | Department of Broadband Communication, Pengcheng Laboratory, Shenzhen 518055, China, Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing 100876, China |
| authorships[4].author.id | https://openalex.org/A5008846998 |
| authorships[4].author.orcid | https://orcid.org/0000-0002-2302-7148 |
| authorships[4].author.display_name | Nan Ma |
| authorships[4].countries | CN |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I4210136793 |
| authorships[4].affiliations[0].raw_affiliation_string | Department of Broadband Communication, Pengcheng Laboratory, Shenzhen 518055, China |
| authorships[4].affiliations[1].institution_ids | https://openalex.org/I139759216 |
| authorships[4].affiliations[1].raw_affiliation_string | Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China |
| authorships[4].institutions[0].id | https://openalex.org/I139759216 |
| authorships[4].institutions[0].ror | https://ror.org/04w9fbh59 |
| authorships[4].institutions[0].type | education |
| authorships[4].institutions[0].lineage | https://openalex.org/I139759216 |
| authorships[4].institutions[0].country_code | CN |
| authorships[4].institutions[0].display_name | Beijing University of Posts and Telecommunications |
| authorships[4].institutions[1].id | https://openalex.org/I4210136793 |
| authorships[4].institutions[1].ror | https://ror.org/03qdqbt06 |
| authorships[4].institutions[1].type | facility |
| authorships[4].institutions[1].lineage | https://openalex.org/I4210136793 |
| authorships[4].institutions[1].country_code | CN |
| authorships[4].institutions[1].display_name | Peng Cheng Laboratory |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Nan Ma |
| authorships[4].is_corresponding | False |
| authorships[4].raw_affiliation_strings | Department of Broadband Communication, Pengcheng Laboratory, Shenzhen 518055, China, Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China |
| authorships[5].author.id | https://openalex.org/A5009164482 |
| authorships[5].author.orcid | https://orcid.org/0000-0003-2608-775X |
| authorships[5].author.display_name | Shuguang Cui |
| authorships[5].countries | CN |
| authorships[5].affiliations[0].institution_ids | https://openalex.org/I4210116924 |
| authorships[5].affiliations[0].raw_affiliation_string | School of Science and Engineering (SSE) and the Future Network of Intelligent Institute (FNii), The Chinese University of Hong Kong (Shenzhen), Shenzhen 518172, China |
| authorships[5].affiliations[1].institution_ids | https://openalex.org/I4210136793 |
| authorships[5].affiliations[1].raw_affiliation_string | Department of Broadband Communication, Pengcheng Laboratory, Shenzhen 518055, China |
| authorships[5].institutions[0].id | https://openalex.org/I4210116924 |
| authorships[5].institutions[0].ror | https://ror.org/02d5ks197 |
| authorships[5].institutions[0].type | education |
| authorships[5].institutions[0].lineage | https://openalex.org/I177725633, https://openalex.org/I180726961, https://openalex.org/I4210116924 |
| authorships[5].institutions[0].country_code | CN |
| authorships[5].institutions[0].display_name | Chinese University of Hong Kong, Shenzhen |
| authorships[5].institutions[1].id | https://openalex.org/I4210136793 |
| authorships[5].institutions[1].ror | https://ror.org/03qdqbt06 |
| authorships[5].institutions[1].type | facility |
| authorships[5].institutions[1].lineage | https://openalex.org/I4210136793 |
| authorships[5].institutions[1].country_code | CN |
| authorships[5].institutions[1].display_name | Peng Cheng Laboratory |
| authorships[5].author_position | middle |
| authorships[5].raw_author_name | Shuguang Cui |
| authorships[5].is_corresponding | False |
| authorships[5].raw_affiliation_strings | Department of Broadband Communication, Pengcheng Laboratory, Shenzhen 518055, China, School of Science and Engineering (SSE) and the Future Network of Intelligent Institute (FNii), The Chinese University of Hong Kong (Shenzhen), Shenzhen 518172, China |
| authorships[6].author.id | https://openalex.org/A5100405787 |
| authorships[6].author.orcid | https://orcid.org/0000-0002-0269-104X |
| authorships[6].author.display_name | Ping Zhang |
| authorships[6].countries | CN |
| authorships[6].affiliations[0].institution_ids | https://openalex.org/I4210136793 |
| authorships[6].affiliations[0].raw_affiliation_string | Department of Broadband Communication, Pengcheng Laboratory, Shenzhen 518055, China |
| authorships[6].affiliations[1].institution_ids | https://openalex.org/I139759216 |
| authorships[6].affiliations[1].raw_affiliation_string | Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China |
| authorships[6].institutions[0].id | https://openalex.org/I139759216 |
| authorships[6].institutions[0].ror | https://ror.org/04w9fbh59 |
| authorships[6].institutions[0].type | education |
| authorships[6].institutions[0].lineage | https://openalex.org/I139759216 |
| authorships[6].institutions[0].country_code | CN |
| authorships[6].institutions[0].display_name | Beijing University of Posts and Telecommunications |
| authorships[6].institutions[1].id | https://openalex.org/I4210136793 |
| authorships[6].institutions[1].ror | https://ror.org/03qdqbt06 |
| authorships[6].institutions[1].type | facility |
| authorships[6].institutions[1].lineage | https://openalex.org/I4210136793 |
| authorships[6].institutions[1].country_code | CN |
| authorships[6].institutions[1].display_name | Peng Cheng Laboratory |
| authorships[6].author_position | last |
| authorships[6].raw_author_name | Ping Zhang |
| authorships[6].is_corresponding | False |
| authorships[6].raw_affiliation_strings | Department of Broadband Communication, Pengcheng Laboratory, Shenzhen 518055, China, Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://www.mdpi.com/1099-4300/27/6/651/pdf?version=1750245143 |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Extended Blahut–Arimoto Algorithm for Semantic Rate-Distortion Function |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T12131 |
| primary_topic.field.id | https://openalex.org/fields/17 |
| primary_topic.field.display_name | Computer Science |
| primary_topic.score | 0.9998999834060669 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1702 |
| primary_topic.subfield.display_name | Artificial Intelligence |
| primary_topic.display_name | Wireless Signal Modulation Classification |
| related_works | https://openalex.org/W2328889547, https://openalex.org/W3003858543, https://openalex.org/W1969547578, https://openalex.org/W4312306082, https://openalex.org/W2378029901, https://openalex.org/W2171488351, https://openalex.org/W3023793255, https://openalex.org/W2358848605, https://openalex.org/W4236414678, https://openalex.org/W2790816803 |
| cited_by_count | 1 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 1 |
| locations_count | 4 |
| best_oa_location.id | doi:10.3390/e27060651 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S195231649 |
| best_oa_location.source.issn | 1099-4300 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 1099-4300 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | Entropy |
| best_oa_location.source.host_organization | https://openalex.org/P4310310987 |
| best_oa_location.source.host_organization_name | Multidisciplinary Digital Publishing Institute |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310310987 |
| best_oa_location.source.host_organization_lineage_names | Multidisciplinary Digital Publishing Institute |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | https://www.mdpi.com/1099-4300/27/6/651/pdf?version=1750245143 |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Entropy |
| best_oa_location.landing_page_url | https://doi.org/10.3390/e27060651 |
| primary_location.id | doi:10.3390/e27060651 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S195231649 |
| primary_location.source.issn | 1099-4300 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 1099-4300 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | Entropy |
| primary_location.source.host_organization | https://openalex.org/P4310310987 |
| primary_location.source.host_organization_name | Multidisciplinary Digital Publishing Institute |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310310987 |
| primary_location.source.host_organization_lineage_names | Multidisciplinary Digital Publishing Institute |
| primary_location.license | cc-by |
| primary_location.pdf_url | https://www.mdpi.com/1099-4300/27/6/651/pdf?version=1750245143 |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Entropy |
| primary_location.landing_page_url | https://doi.org/10.3390/e27060651 |
| publication_date | 2025-06-18 |
| publication_year | 2025 |
| referenced_works | https://openalex.org/W4286224510, https://openalex.org/W4249477869, https://openalex.org/W2963174256, https://openalex.org/W3036851434, https://openalex.org/W2946889564, https://openalex.org/W3166791908, https://openalex.org/W1995875735, https://openalex.org/W1945834810, https://openalex.org/W2135469284, https://openalex.org/W2029236670, https://openalex.org/W2148986322, https://openalex.org/W1494926642, https://openalex.org/W4408083596, https://openalex.org/W2532607215, https://openalex.org/W2154381121, https://openalex.org/W2103145132, https://openalex.org/W2080570118, https://openalex.org/W4376455152, https://openalex.org/W4386075222, https://openalex.org/W4390775519, https://openalex.org/W6861348556, https://openalex.org/W4399803256, https://openalex.org/W2161877964, https://openalex.org/W4401387161, https://openalex.org/W4402680811, https://openalex.org/W4403183268, https://openalex.org/W4388481798, https://openalex.org/W4387717661, https://openalex.org/W4410921937, https://openalex.org/W4313455370 |
| referenced_works_count | 30 |
| abstract_inverted_index.a | 36, 105, 119, 136, 146 |
| abstract_inverted_index.In | 27 |
| abstract_inverted_index.RD | 71, 170 |
| abstract_inverted_index.To | 82 |
| abstract_inverted_index.an | 92, 174 |
| abstract_inverted_index.as | 135 |
| abstract_inverted_index.by | 18, 53, 128 |
| abstract_inverted_index.in | 7, 39, 77 |
| abstract_inverted_index.of | 139, 161 |
| abstract_inverted_index.on | 20, 74, 188 |
| abstract_inverted_index.to | 11, 14, 50, 67, 198 |
| abstract_inverted_index.we | 30, 90 |
| abstract_inverted_index.CUB | 190 |
| abstract_inverted_index.EBA | 98, 143, 163 |
| abstract_inverted_index.For | 165 |
| abstract_inverted_index.SKB | 154, 195 |
| abstract_inverted_index.and | 64, 114, 151, 178 |
| abstract_inverted_index.are | 88 |
| abstract_inverted_index.due | 10 |
| abstract_inverted_index.for | 44, 149 |
| abstract_inverted_index.has | 2 |
| abstract_inverted_index.its | 12, 183 |
| abstract_inverted_index.the | 32, 46, 55, 69, 97, 108, 116, 130, 142, 153, 159, 162, 168, 189 |
| abstract_inverted_index.(BA) | 34 |
| abstract_inverted_index.(RD) | 48 |
| abstract_inverted_index.base | 133 |
| abstract_inverted_index.lead | 197 |
| abstract_inverted_index.than | 23, 182 |
| abstract_inverted_index.that | 95, 123, 193 |
| abstract_inverted_index.this | 28 |
| abstract_inverted_index.with | 100, 104, 118, 173 |
| abstract_inverted_index.(CIT) | 43 |
| abstract_inverted_index.(EBA) | 58 |
| abstract_inverted_index.(SKB) | 134 |
| abstract_inverted_index.based | 73 |
| abstract_inverted_index.exact | 24 |
| abstract_inverted_index.lower | 181 |
| abstract_inverted_index.size. | 155 |
| abstract_inverted_index.sizes | 196 |
| abstract_inverted_index.where | 85 |
| abstract_inverted_index.which | 60 |
| abstract_inverted_index.(SIT). | 81 |
| abstract_inverted_index.extend | 31 |
| abstract_inverted_index.gained | 4 |
| abstract_inverted_index.higher | 199 |
| abstract_inverted_index.larger | 194 |
| abstract_inverted_index.merges | 111 |
| abstract_inverted_index.method | 38 |
| abstract_inverted_index.number | 122, 177 |
| abstract_inverted_index.paper, | 29 |
| abstract_inverted_index.rather | 22 |
| abstract_inverted_index.signal | 25 |
| abstract_inverted_index.theory | 42, 80 |
| abstract_inverted_index.address | 83 |
| abstract_inverted_index.becomes | 179 |
| abstract_inverted_index.dataset | 191 |
| abstract_inverted_index.develop | 91 |
| abstract_inverted_index.improve | 15 |
| abstract_inverted_index.mapping | 76, 117 |
| abstract_inverted_index.maximum | 120 |
| abstract_inverted_index.meaning | 21 |
| abstract_inverted_index.results | 157 |
| abstract_inverted_index.symbols | 113 |
| abstract_inverted_index.updates | 62 |
| abstract_inverted_index.Gaussian | 166 |
| abstract_inverted_index.Semantic | 0 |
| abstract_inverted_index.analysis | 9, 187 |
| abstract_inverted_index.approach | 148 |
| abstract_inverted_index.combines | 96 |
| abstract_inverted_index.extended | 56 |
| abstract_inverted_index.focusing | 19 |
| abstract_inverted_index.function | 72, 171 |
| abstract_inverted_index.instance | 138 |
| abstract_inverted_index.mapping, | 107, 141 |
| abstract_inverted_index.mappings | 87 |
| abstract_inverted_index.provides | 145 |
| abstract_inverted_index.recently | 3 |
| abstract_inverted_index.semantic | 51, 70, 78, 131, 169, 200 |
| abstract_inverted_index.sources, | 167 |
| abstract_inverted_index.specific | 137 |
| abstract_inverted_index.unknown, | 89 |
| abstract_inverted_index.validate | 158 |
| abstract_inverted_index.Numerical | 156 |
| abstract_inverted_index.algorithm | 99, 144 |
| abstract_inverted_index.analyzing | 150 |
| abstract_inverted_index.attention | 6 |
| abstract_inverted_index.calculate | 68 |
| abstract_inverted_index.classical | 40, 184 |
| abstract_inverted_index.computing | 45 |
| abstract_inverted_index.decreases | 172 |
| abstract_inverted_index.framework | 94, 109 |
| abstract_inverted_index.function, | 49 |
| abstract_inverted_index.knowledge | 132 |
| abstract_inverted_index.objective | 125 |
| abstract_inverted_index.potential | 13 |
| abstract_inverted_index.proposing | 54 |
| abstract_inverted_index.satisfies | 124 |
| abstract_inverted_index.scenarios | 84 |
| abstract_inverted_index.simulated | 101 |
| abstract_inverted_index.syntactic | 106, 112 |
| abstract_inverted_index.algorithm, | 35, 59 |
| abstract_inverted_index.algorithm. | 164 |
| abstract_inverted_index.annealing. | 102 |
| abstract_inverted_index.efficiency | 17 |
| abstract_inverted_index.identifies | 115 |
| abstract_inverted_index.increasing | 175 |
| abstract_inverted_index.predicting | 152 |
| abstract_inverted_index.synonymous | 75, 86, 121, 140, 176 |
| abstract_inverted_index.transition | 63 |
| abstract_inverted_index.Initialized | 103 |
| abstract_inverted_index.compression | 202 |
| abstract_inverted_index.considering | 129 |
| abstract_inverted_index.efficiency. | 203 |
| abstract_inverted_index.fundamental | 37 |
| abstract_inverted_index.information | 41, 79 |
| abstract_inverted_index.iteratively | 61 |
| abstract_inverted_index.significant | 5 |
| abstract_inverted_index.theoretical | 8, 147 |
| abstract_inverted_index.Furthermore, | 127 |
| abstract_inverted_index.constraints. | 126 |
| abstract_inverted_index.counterpart. | 185 |
| abstract_inverted_index.demonstrates | 192 |
| abstract_inverted_index.optimization | 93 |
| abstract_inverted_index.Additionally, | 186 |
| abstract_inverted_index.communication | 1, 16, 52, 201 |
| abstract_inverted_index.distributions | 66 |
| abstract_inverted_index.effectiveness | 160 |
| abstract_inverted_index.progressively | 110 |
| abstract_inverted_index.significantly | 180 |
| abstract_inverted_index.reconstruction | 65 |
| abstract_inverted_index.rate-distortion | 47 |
| abstract_inverted_index.reconstruction. | 26 |
| abstract_inverted_index.Blahut–Arimoto | 33, 57 |
| cited_by_percentile_year.max | 95 |
| cited_by_percentile_year.min | 91 |
| corresponding_author_ids | https://openalex.org/A5008455605 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 7 |
| corresponding_institution_ids | https://openalex.org/I139759216, https://openalex.org/I4210136793 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/4 |
| sustainable_development_goals[0].score | 0.4099999964237213 |
| sustainable_development_goals[0].display_name | Quality Education |
| citation_normalized_percentile.value | 0.94610508 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |