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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2506.21126 |
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| _version_ | 1866912451331620864 |
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| author | Guo, Jiajia Cui, Yiming Jin, Shi |
| author_facet | Guo, Jiajia Cui, Yiming Jin, Shi |
| contents | Artificial intelligence (AI) substantially enhances channel state information (CSI) acquisition performance but is limited by its reliance on single-modality information and deployment challenges, particularly in dataset collection. This paper investigates the use of semantic-aware digital twin (DT) to enhance AI-based CSI acquisition. We first briefly introduce the motivation and recent advancements in AI-driven CSI acquisition and semantic-aware DT employment for air interfaces. Then, we thoroughly explore how semantic-aware DT can bolster AI-based CSI acquisition. We categorizes the semantic-aware DT for AI-based CSI acquisition into two classes: enhancing AI-based CSI acquisition through integration with DT and using DT to aid AI-based CSI deployment. Potential integration frameworks are introduced in detail. Finally, we conclude by outlining potential research directions within the semantic-aware DT-assisted AI-based CSI acquisition. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_21126 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Semantic-aware Digital Twin for AI-based CSI Acquisition Guo, Jiajia Cui, Yiming Jin, Shi Information Theory Artificial intelligence (AI) substantially enhances channel state information (CSI) acquisition performance but is limited by its reliance on single-modality information and deployment challenges, particularly in dataset collection. This paper investigates the use of semantic-aware digital twin (DT) to enhance AI-based CSI acquisition. We first briefly introduce the motivation and recent advancements in AI-driven CSI acquisition and semantic-aware DT employment for air interfaces. Then, we thoroughly explore how semantic-aware DT can bolster AI-based CSI acquisition. We categorizes the semantic-aware DT for AI-based CSI acquisition into two classes: enhancing AI-based CSI acquisition through integration with DT and using DT to aid AI-based CSI deployment. Potential integration frameworks are introduced in detail. Finally, we conclude by outlining potential research directions within the semantic-aware DT-assisted AI-based CSI acquisition. |
| title | Semantic-aware Digital Twin for AI-based CSI Acquisition |
| topic | Information Theory |
| url | https://arxiv.org/abs/2506.21126 |