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

Research output: Contribution to Journal/MagazineJournal articlepeer-review

E-pub ahead of print
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<mark>Journal publication date</mark>23/12/2024
<mark>Journal</mark>IEEE Network
Publication StatusE-pub ahead of print
Early online date23/12/24
<mark>Original language</mark>English

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.