Optimizing 6G Integrated Sensing and Communications (ISAC) via Expert Networks
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arXiv
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866929369474138112 |
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| author | Wang, Jiacheng Du, Hongyang Sun, Geng Kang, Jiawen Zhou, Haibo Niyato, Dusit Chen, Jiming |
| author_facet | Wang, Jiacheng Du, Hongyang Sun, Geng Kang, Jiawen Zhou, Haibo Niyato, Dusit Chen, Jiming |
| contents | Integrated Sensing and Communications (ISAC) is one of the core technologies of 6G, which combines sensing and communication functions into a single system. However, limited computing and storage resources make it impractical to combine multiple sensing models into a single device, constraining the system's function and performance. Therefore, this article proposes enhancing ISAC with the mixture of experts (MoE) architecture. Rigorously, we first investigate ISAC and MoE, including their concepts, advantages, and applications. Then, we explore how MoE can enhance ISAC from the perspectives of signal processing and network optimization. Building on this, we propose an MoE based ISAC framework, which uses a gating network to selectively activate multiple experts in handling sensing tasks under given communication conditions, thereby improving the overall performance. The case study demonstrates that the proposed framework can effectively increase the accuracy and robustness in detecting targets by using wireless communication signal, providing strong support for the practical deployment and applications of the ISAC system. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_00408 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Optimizing 6G Integrated Sensing and Communications (ISAC) via Expert Networks Wang, Jiacheng Du, Hongyang Sun, Geng Kang, Jiawen Zhou, Haibo Niyato, Dusit Chen, Jiming Signal Processing Integrated Sensing and Communications (ISAC) is one of the core technologies of 6G, which combines sensing and communication functions into a single system. However, limited computing and storage resources make it impractical to combine multiple sensing models into a single device, constraining the system's function and performance. Therefore, this article proposes enhancing ISAC with the mixture of experts (MoE) architecture. Rigorously, we first investigate ISAC and MoE, including their concepts, advantages, and applications. Then, we explore how MoE can enhance ISAC from the perspectives of signal processing and network optimization. Building on this, we propose an MoE based ISAC framework, which uses a gating network to selectively activate multiple experts in handling sensing tasks under given communication conditions, thereby improving the overall performance. The case study demonstrates that the proposed framework can effectively increase the accuracy and robustness in detecting targets by using wireless communication signal, providing strong support for the practical deployment and applications of the ISAC system. |
| title | Optimizing 6G Integrated Sensing and Communications (ISAC) via Expert Networks |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2406.00408 |