Communication and Control Co-Design in 6G: Sequential Decision-Making with LLMs
<|reference_start|>Communication and Control Co-Design in 6G: Sequential Decision-Making with LLMs: This article investigates a control system within the context of six-generation wireless networks. The control performance optimization confronts the technical challenges that arise from the intricate interactions between communication and control sub-systems, asking for a co-design. Accounting for the system dynamics, we formulate the sequential co-design decision-makings of communication and control over the 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 potentials from our proposed learning framework. Furthermore, we discuss the open issues remaining to make our proposed offline learning framework feasible for real-world implementations, and highlight the research directions for future explorations.<|reference_end|>
@article{chen2024communication,
    title={Communication and Control Co-Design in 6G: Sequential Decision-Making
  with LLMs},
    author={Xianfu Chen and Celimuge Wu and Yi Shen and Yusheng Ji and Tsutomu
  Yoshinaga and Qiang Ni and Charilaos C. Zarakovitis and Honggang Zhang},
    journal={arXiv preprint arXiv:2407.06227},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.06227},
    primaryClass={eess.SY cs.AI cs.SY}
}