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Communication and Control Co-Design in 6G: Sequential Decision-Making with LLMs

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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Communication and Control Co-Design in 6G: Sequential Decision-Making with LLMs. / Chen, Xianfu; Wu, Celimuge; Shen, Yi et al.
In: IEEE Network, 23.12.2024.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Chen, X, Wu, C, Shen, Y, Ji, Y, Yoshinaga, T, Ni, Q, Zarakovitis, CC & Zhang, H 2024, 'Communication and Control Co-Design in 6G: Sequential Decision-Making with LLMs', IEEE Network. https://doi.org/10.1109/mnet.2024.3520983

APA

Chen, X., Wu, C., Shen, Y., Ji, Y., Yoshinaga, T., Ni, Q., Zarakovitis, C. C., & Zhang, H. (2024). Communication and Control Co-Design in 6G: Sequential Decision-Making with LLMs. IEEE Network. Advance online publication. https://doi.org/10.1109/mnet.2024.3520983

Vancouver

Chen X, Wu C, Shen Y, Ji Y, Yoshinaga T, Ni Q et al. Communication and Control Co-Design in 6G: Sequential Decision-Making with LLMs. IEEE Network. 2024 Dec 23. Epub 2024 Dec 23. doi: 10.1109/mnet.2024.3520983

Author

Chen, Xianfu ; Wu, Celimuge ; Shen, Yi et al. / Communication and Control Co-Design in 6G : Sequential Decision-Making with LLMs. In: IEEE Network. 2024.

Bibtex

@article{ad6cb8a6c9d044918e355ff3dd7ca32a,
title = "Communication and Control Co-Design in 6G: Sequential Decision-Making with LLMs",
abstract = "This article investigates a control system within the context of sixth-generation wireless networks. The remote control performance optimization confronts the technical challenges that arise from the intricate interactions between communication and control sub-systems, asking for a co-design. Considering the system dynamics, we formulate the sequential co-design decision-makings of communication and control over a discrete time horizon as a Markov decision process, for which a practical offline learning framework is proposed. Our proposed framework integrates large language models into the elements of reinforcement learning. We present a case study on the age of semantics-aware communication and control co-design to showcase the potential of our proposed learning framework. Furthermore, we discuss the open issues remaining to make our offline learning framework feasible for real-world implementations and highlight the research directions for future explorations.",
author = "Xianfu Chen and Celimuge Wu and Yi Shen and Yusheng Ji and Tsutomu Yoshinaga and Qiang Ni and Zarakovitis, {Charilaos C.} and Honggang Zhang",
year = "2024",
month = dec,
day = "23",
doi = "10.1109/mnet.2024.3520983",
language = "English",
journal = "IEEE Network",
issn = "0890-8044",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

RIS

TY - JOUR

T1 - Communication and Control Co-Design in 6G

T2 - Sequential Decision-Making with LLMs

AU - Chen, Xianfu

AU - Wu, Celimuge

AU - Shen, Yi

AU - Ji, Yusheng

AU - Yoshinaga, Tsutomu

AU - Ni, Qiang

AU - Zarakovitis, Charilaos C.

AU - Zhang, Honggang

PY - 2024/12/23

Y1 - 2024/12/23

N2 - This article investigates a control system within the context of sixth-generation wireless networks. The remote control performance optimization confronts the technical challenges that arise from the intricate interactions between communication and control sub-systems, asking for a co-design. Considering the system dynamics, we formulate the sequential co-design decision-makings of communication and control over a discrete time horizon as a Markov decision process, for which a practical offline learning framework is proposed. Our proposed framework integrates large language models into the elements of reinforcement learning. We present a case study on the age of semantics-aware communication and control co-design to showcase the potential of our proposed learning framework. Furthermore, we discuss the open issues remaining to make our offline learning framework feasible for real-world implementations and highlight the research directions for future explorations.

AB - This article investigates a control system within the context of sixth-generation wireless networks. The remote control performance optimization confronts the technical challenges that arise from the intricate interactions between communication and control sub-systems, asking for a co-design. Considering the system dynamics, we formulate the sequential co-design decision-makings of communication and control over a discrete time horizon as a Markov decision process, for which a practical offline learning framework is proposed. Our proposed framework integrates large language models into the elements of reinforcement learning. We present a case study on the age of semantics-aware communication and control co-design to showcase the potential of our proposed learning framework. Furthermore, we discuss the open issues remaining to make our offline learning framework feasible for real-world implementations and highlight the research directions for future explorations.

U2 - 10.1109/mnet.2024.3520983

DO - 10.1109/mnet.2024.3520983

M3 - Journal article

JO - IEEE Network

JF - IEEE Network

SN - 0890-8044

ER -