TOIB: Task-Oriented Orthogonalised Information Bottleneck for Distributed Semantic Communication
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arXiv
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| Autores principales: | , , , , |
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| Formato: | Preprint |
| Publicado: |
2026
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| _version_ | 1866908958075125760 |
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| author | Wang, Jiaxiang Yang, Zhaohui Ding, Yahao Hu, Ye Shikh-Bahaei, Mohammad |
| author_facet | Wang, Jiaxiang Yang, Zhaohui Ding, Yahao Hu, Ye Shikh-Bahaei, Mohammad |
| contents | Task-oriented semantic communication emerges as a crucial paradigm for next-generation wireless networks, aiming to efficiently transmit task-relevant information while reducing interference and redundancy across multiple users. Existing information bottleneck (IB)-based frameworks predominantly focus on single-user scenarios, neglecting cross-user semantic interference in distributed semantic communications. To overcome this limitation, we propose a task-oriented orthogonalised information bottleneck (TOIB) approach, explicitly designed for distributed semantic communication systems. By introducing task-conditioned latent variables, TOIB adaptively balances semantic sufficiency, semantic compression, and inter-user semantic orthogonality. Extensive simulations conducted on classification tasks demonstrate that TOIB consistently achieves superior classification accuracy across various signal-to-noise ratio (SNR) regimes compared to traditional IB and deep joint source-channel coding (JSCC) methods. Specifically, the proposed method significantly enhances robustness under harsh low-SNR conditions and effectively suppresses cross-user semantic interference, as validated by cross-decoding accuracy metrics. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_11053 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | TOIB: Task-Oriented Orthogonalised Information Bottleneck for Distributed Semantic Communication Wang, Jiaxiang Yang, Zhaohui Ding, Yahao Hu, Ye Shikh-Bahaei, Mohammad Signal Processing Task-oriented semantic communication emerges as a crucial paradigm for next-generation wireless networks, aiming to efficiently transmit task-relevant information while reducing interference and redundancy across multiple users. Existing information bottleneck (IB)-based frameworks predominantly focus on single-user scenarios, neglecting cross-user semantic interference in distributed semantic communications. To overcome this limitation, we propose a task-oriented orthogonalised information bottleneck (TOIB) approach, explicitly designed for distributed semantic communication systems. By introducing task-conditioned latent variables, TOIB adaptively balances semantic sufficiency, semantic compression, and inter-user semantic orthogonality. Extensive simulations conducted on classification tasks demonstrate that TOIB consistently achieves superior classification accuracy across various signal-to-noise ratio (SNR) regimes compared to traditional IB and deep joint source-channel coding (JSCC) methods. Specifically, the proposed method significantly enhances robustness under harsh low-SNR conditions and effectively suppresses cross-user semantic interference, as validated by cross-decoding accuracy metrics. |
| title | TOIB: Task-Oriented Orthogonalised Information Bottleneck for Distributed Semantic Communication |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2604.11053 |