物联网学报2025，Vol.9Issue(2)：82-94,13.DOI:10.11959/j.issn.2096-3750.2025.00481
基于Decision Transformer模型的5G基站节能控制策略优化新范式研究
Research on the new paradigm for optimizing 5G base station energy-saving control strategies utilizing the Decision Transformer model
摘要
Abstract
With the ongoing proliferation of 5G networks,there has been a surge in the deployment of base station equip-ment.This trend has not only given rise to new demands within the telecommunications industry for enhancing the overall energy efficiency of 5G base stations and achieving energy conservation and emission reduction but also imposed higher standards on related manufacturers.While traditional reinforcement learning(RL)techniques hold promise for optimizing energy-saving strategies for 5G base stations,they require extensive environmental interactions and model training time.Moreover,in the face of dynamically changing base station operating environments,the variability in state and action spaces can make it difficult for RL to learn effective strategies,and the generalization ability of traditional RL models is also limited.To address these challenges,a new framework for optimizing 5G base station energy-saving control strate-gies based on the Decision Transformer(DT)model was innovatively proposed.The framework decouples the state and action spaces corresponding to each base station for different scenario tasks and improves the original DT model based on the trajectory priors to optimize the expected return of the model through the prior information of the trajectory data.Simulation results demonstrate that compared to other RL algorithms,the proposed method can significantly reduce system power consumption while ensuring the quality of service for users,and it can adapt to unknown tasks without retraining,showcasing the distinct advantages and application potential of our approach in the context of 5G base station energy-saving decision-making.关键词
5G/基站节能/策略优化/强化学习/DT模型Key words
5G/energy saving of base station/strategy optimization/reinforcement learning/Decision Transformer model分类
信息技术与安全科学引用本文复制引用
夏鹏程,朱银涛,于霄,何怡,倪艺洋..基于Decision Transformer模型的5G基站节能控制策略优化新范式研究[J].物联网学报,2025,9(2):82-94,13.基金项目
国家自然科学基金资助项目(No.62471204) （No.62471204）
江苏省基础研究计划(自然科学基金)前沿引领技术基础研究专项(No.BK20212001) （自然科学基金）
江苏省高等学校基础科学(自然科学)研究重大项目(No.24KJA510003)The National Natural Science Foundation of China(No.62471204),The Natural Science Foundation on Frontier Leading Technology Basic Research Project of Jiangsu(No.BK20212001),Major Natural Science Foundation of the Higher Education Institutions of Jiangsu Province(No.24KJA510003) （自然科学）
