ETRI Knowledge Sharing Platform : LLM-Assisted Network Management for Digital Twin-Enabled 5G Systems

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Conference Paper LLM-Assisted Network Management for Digital Twin-Enabled 5G Systems

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Authors: Yukai Wang, Janghee Woo, Gyeong-June Hahm, Kyung-Yul Cheon, Hyenyeon Kwon, Seungkeun Park, Sang-Woon Jeon

Citation: International Conference on Ubiquitous and Future Networks (ICUFN) 2026, pp.1087-1089

Abstract: Efficient long-term network evolution is becoming increasingly critical in dense 5G-Advanced and beyond cellular systems, where persistent traffic imbalances and localized congestion pose significant challenges that conventional short-term radio resource management alone cannot fully mitigate. This paper proposes a digital twin (DT)-enabled non-real-time (NRT) network evolution framework integrated with a large language model (LLM). Within this architecture, the digital twin provides a high-fidelity, controllable environment for evaluating infrastructure actions, while the LLM serves as a strategic orchestration engine that recommends cost-efficient network upgrades based on observed network states. Unlike traditional optimization methods that require exhaustive mathematical reformulations for each specific scenario, the proposed framework leverages the reasoning capabilities of LLMs to interpret operator objectives and constraints in natural language, generating structured evolution plans. The considered NRT action space encompasses antenna upgrades, bandwidth expansion, and new base station (BS) deployment. A techno-economic formulation is introduced to jointly evaluate load reduction performance and overall economic expenditure. Numerical results in a dense cellular scenario demonstrate that the framework effectively reduces peak resource utilization and provides diverse, coordinated evolution strategies tailored to varying network conditions.

Keyword: 5G-Advanced, digital twin, Large language model, network evolution, non-real-time optimization, resource usage, techno-economic analysis

KSP Keywords: 5G system, Action space, Cellular system, Cost-efficient, Digital Twin, High-fidelity, Language Models, Natural language, Network management, Persistent traffic, Radio resource management(RRM)