Semantic Communications using Foundation Models: Design Approaches and Open Issues
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2023
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| _version_ | 1866910669321797632 |
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| author | Jiang, Peiwen Wen, Chao-Kai Yi, Xinping Li, Xiao Jin, Shi Zhang, Jun |
| author_facet | Jiang, Peiwen Wen, Chao-Kai Yi, Xinping Li, Xiao Jin, Shi Zhang, Jun |
| contents | Foundation models (FMs), including large language models, have become increasingly popular due to their wide-ranging applicability and ability to understand human-like semantics. While previous research has explored the use of FMs in semantic communications to improve semantic extraction and reconstruction, the impact of these models on different system levels, considering computation and memory complexity, requires further analysis. This study focuses on integrating FMs at the effectiveness, semantic, and physical levels, using universal knowledge to profoundly transform system design. Additionally, it examines the use of compact models to balance performance and complexity, comparing three separate approaches that employ FMs. Ultimately, the study highlights unresolved issues in the field that need addressing. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2309_13315 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Semantic Communications using Foundation Models: Design Approaches and Open Issues Jiang, Peiwen Wen, Chao-Kai Yi, Xinping Li, Xiao Jin, Shi Zhang, Jun Signal Processing Image and Video Processing Foundation models (FMs), including large language models, have become increasingly popular due to their wide-ranging applicability and ability to understand human-like semantics. While previous research has explored the use of FMs in semantic communications to improve semantic extraction and reconstruction, the impact of these models on different system levels, considering computation and memory complexity, requires further analysis. This study focuses on integrating FMs at the effectiveness, semantic, and physical levels, using universal knowledge to profoundly transform system design. Additionally, it examines the use of compact models to balance performance and complexity, comparing three separate approaches that employ FMs. Ultimately, the study highlights unresolved issues in the field that need addressing. |
| title | Semantic Communications using Foundation Models: Design Approaches and Open Issues |
| topic | Signal Processing Image and Video Processing |
| url | https://arxiv.org/abs/2309.13315 |