article · ArXiv.org · 2026

Large Language Model (LLM)-enabled Reinforcement Learning for Wireless Network Optimization

Jie Zheng, Ruichen Zhang, Dusit Niyato, Haijun Zhang, Jiacheng Wang, Hongyang Du, Jiawen Kang, Zehui Xiong

Cited by 0Open access

Abstract

Enhancing future wireless networks presents a significant challenge for networking systems due to diverse user demands and the emergence of 6G technology. While reinforcement learning (RL) is a powerful framework, it often encounters difficulties with high-dimensional state spaces and complex environments, leading to substantial computational demands, distributed intelligence, and potentially inconsistent outcomes. Large language models (LLMs), with their extensive pretrained knowledge and advanced reasoning capabilities, offer promising tools to enhance RL in optimizing 6G wireless networks. We explore RL models augmented by LLMs, emphasizing their roles and the potential benefits of their synergy in wireless network optimization. We then examine LLM-enabled RL across various protocol layers: physical, data link, network, transport, and application layers. Additionally, we propose an LLM-assisted state representation and semantic extraction to enhance the multi-agent reinforcement learning (MARL) framework. This approach is applied to service migration and request routing, as well as topology graph generation in unmanned aerial vehicle (UAV)-satellite networks. Through case studies, we demonstrate that our framework effectively performs optimization of wireless network. Finally, we outline prospective research directions for LLM-enabled RL in wireless network optimization.

Cite this paper

APA 7

Zheng, J., Zhang, R., Niyato, D., Zhang, H., Wang, J., Du, H., Kang, J., & Xiong, Z. (2026). Large Language Model (LLM)-enabled Reinforcement Learning for Wireless Network Optimization. ArXiv.org.

MLA 9

Zheng, Jie, et al. “Large Language Model (LLM)-enabled Reinforcement Learning for Wireless Network Optimization.” ArXiv.org, 2026.

Chicago

Zheng, Jie, Ruichen Zhang, Dusit Niyato, Haijun Zhang, Jiacheng Wang, Hongyang Du, Jiawen Kang, and Zehui Xiong. 2026. “Large Language Model (LLM)-enabled Reinforcement Learning for Wireless Network Optimization.” ArXiv.org.

Harvard

Zheng, J. et al. (2026) ‘Large Language Model (LLM)-enabled Reinforcement Learning for Wireless Network Optimization’, ArXiv.org.

BibTeX

@article{zheng2026large,
  title = {{Large Language Model (LLM)-enabled Reinforcement Learning for Wireless Network Optimization}},
  author = {Zheng, Jie and Zhang, Ruichen and Niyato, Dusit and Zhang, Haijun and Wang, Jiacheng and Du, Hongyang and Kang, Jiawen and Xiong, Zehui},
  journal = {ArXiv.org},
  year = {2026}
}

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