Dual-LLM integration with reconfigurable intelligent surface for healthcare networks

Kurma, S, Singh, K, Paul, A, Mumtaz, S ORCID: https://orcid.org/0000-0001-6364-6149 and Li, C-P, 2025. Dual-LLM integration with reconfigurable intelligent surface for healthcare networks. IEEE Transactions on Communications. ISSN 0090-6778

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Abstract

The increasing complexity of real-time healthcare necessitates intelligent systems for dynamic data management and personalized assistance. This paper proposes a novel dual-LLM framework that integrates large language models (LLMs) into wireless healthcare networks. The first LLM powers an interactive artificial intelligence module (IAIM) embedded within a mobile edge computing (MEC) environment, which dynamically optimizes user-specific data routing and reconfigurable intelligent surface (RIS) configurations via a modified proximal policy optimization (PPO) algorithm. A novel Greedy Look-Ahead Algorithm (GLAA) is introduced for real-time path selection based on signal strength, emergency factors, and user-specific parameters. The second LLM, utilizing a retrieval-augmented generation (RAG) approach, serves as a personalized healthcare chat assistant that delivers context-aware patient support using real-time and historical data. Simulation results demonstrate that the proposed IAIM achieves a 9.6% reduction in network overhead compared to manual modeling and reduces latency by up to 52.5% over baseline PPO approaches, thus enabling enhanced user experience and responsiveness in healthcare systems.

Item Type:	Journal article
Publication Title:	IEEE Transactions on Communications
Creators:	Kurma, S., Singh, K., Paul, A., Mumtaz, S. and Li, C.-P.
Publisher:	Institute of Electrical and Electronics Engineers (IEEE)
Date:	2025
ISSN:	0090-6778
Identifiers:	Number Type 10.1109/tcomm.2025.3587065 DOI 2478064 Other
Rights:	© 2025 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
Divisions:	Schools > School of Science and Technology
Record created by:	Jeremy Silvester
Date Added:	30 Jul 2025 08:50
Last Modified:	30 Jul 2025 08:50
URI:	https://irep.ntu.ac.uk/id/eprint/54058

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