Advances and challenges in semantic communications: A systematic review
Inspired by the recent success of machine learning (ML), the concept of semantic communication introduced by Weaver in 1949 has gained significant attention and has become a promising research direction. Unlike conventional communication systems, semantic communication emphasizes the precise retriev...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Science Press
2023-12-01
|
| Series: | National Science Open |
| Subjects: | |
| Online Access: | https://www.sciengine.com/doi/10.1360/nso/20230029 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850070815910920192 |
|---|---|
| author | Zhang Ping Liu Yiming Song Yile Zhang Jiaxiang |
| author_facet | Zhang Ping Liu Yiming Song Yile Zhang Jiaxiang |
| author_sort | Zhang Ping |
| collection | DOAJ |
| description | Inspired by the recent success of machine learning (ML), the concept of semantic communication introduced by Weaver in 1949 has gained significant attention and has become a promising research direction. Unlike conventional communication systems, semantic communication emphasizes the precise retrieval of conveyed meaning from the source to the receiver, rather than focusing on the accurate transmission of symbols. Thus, semantic communication can achieve a significant gain in source data compression, alleviate communication bandwidth pressure, and support new intelligent services, which is envisioned as a crucial enabler of future sixth-generation (6G) networks. In this review, we critically summarize the advances made in semantic information and semantic communications, including theory, architecture, and potential applications. Moreover, we deeply explore the major challenges in developing semantic communications and present the development prospects, aiming to prompt further scientific and industrial advances in semantic communications. |
| format | Article |
| id | doaj-art-27c233e498f7448c80c60020fa45505f |
| institution | DOAJ |
| issn | 2097-1168 |
| language | English |
| publishDate | 2023-12-01 |
| publisher | Science Press |
| record_format | Article |
| series | National Science Open |
| spelling | doaj-art-27c233e498f7448c80c60020fa45505f2025-08-20T02:47:27ZengScience PressNational Science Open2097-11682023-12-01310.1360/nso/20230029eb33e642Advances and challenges in semantic communications: A systematic reviewZhang Ping0Liu Yiming1Song Yile2Zhang Jiaxiang3["State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China","Department of Broadband Communication, Peng Cheng Laboratory, Shenzhen 518055, China"]["State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China"]["State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China"]["State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China"]Inspired by the recent success of machine learning (ML), the concept of semantic communication introduced by Weaver in 1949 has gained significant attention and has become a promising research direction. Unlike conventional communication systems, semantic communication emphasizes the precise retrieval of conveyed meaning from the source to the receiver, rather than focusing on the accurate transmission of symbols. Thus, semantic communication can achieve a significant gain in source data compression, alleviate communication bandwidth pressure, and support new intelligent services, which is envisioned as a crucial enabler of future sixth-generation (6G) networks. In this review, we critically summarize the advances made in semantic information and semantic communications, including theory, architecture, and potential applications. Moreover, we deeply explore the major challenges in developing semantic communications and present the development prospects, aiming to prompt further scientific and industrial advances in semantic communications.https://www.sciengine.com/doi/10.1360/nso/20230029semantic communicationssemantic information6Gartificial intelligencedeep learning |
| spellingShingle | Zhang Ping Liu Yiming Song Yile Zhang Jiaxiang Advances and challenges in semantic communications: A systematic review National Science Open semantic communications semantic information 6G artificial intelligence deep learning |
| title | Advances and challenges in semantic communications: A systematic review |
| title_full | Advances and challenges in semantic communications: A systematic review |
| title_fullStr | Advances and challenges in semantic communications: A systematic review |
| title_full_unstemmed | Advances and challenges in semantic communications: A systematic review |
| title_short | Advances and challenges in semantic communications: A systematic review |
| title_sort | advances and challenges in semantic communications a systematic review |
| topic | semantic communications semantic information 6G artificial intelligence deep learning |
| url | https://www.sciengine.com/doi/10.1360/nso/20230029 |
| work_keys_str_mv | AT zhangping advancesandchallengesinsemanticcommunicationsasystematicreview AT liuyiming advancesandchallengesinsemanticcommunicationsasystematicreview AT songyile advancesandchallengesinsemanticcommunicationsasystematicreview AT zhangjiaxiang advancesandchallengesinsemanticcommunicationsasystematicreview |