报告详情
5G and Beyond Networks for the Sustainable Development Goals: A Heterogeneous Energy-Aware Framework with Deep Reinforcement Learning-Based Resource Optimization
编号：110
访问权限：仅限参会人
更新：2026-11-10 16:47:40 浏览：8次
Online
报告开始：2026年11月21日 16:30（Asia/Kolkata）
报告时间：15min
所在会场：[S5] Data Science and Intelligent Analytics [S5-2] Data Science and Intelligent Analytics
暂无文件
摘要
Abstract- However, the rapid expansion of fifth-generation (5G) and emerging beyond-5G (B5G) wireless networks offers an unprecedented window for speeding progress across all seventeen United Nations Sustainable Development Goals (SDGs). Yet, the energy consumption of dense base-station deployments (including their exterminated proliferation in rural and low-income regions), and above all the inefficiency of spectrum utilization all together prevent us from achieving this potential. In this context, we propose a new research direction that offers an original Heterogeneous Energy-Aware Framework (HEAF) combines multi-tier network slicing, renewable energy harvesting and a resource orchestration engine based on Deep Reinforcement Learning (DRL) to achieve joint optimization of spectral efficiency, energy efficiency and Quality-of-Service (QoS) over heterogeneous 5G/B5G deployments. The model suggested is a compounding utility function capturing SDG-aligned indicators (connectivity coverage, carbon footprint, from the 2030 Agenda and inclusive access index), as well as non-convex optimization solved by a Proximal Policy Optimization (PPO) agent on graphs for state representation of its radio access network. The extensive simulations based on 3GPP-compliant channel models and actual SDG indicator datasets show that HEAF gains up to 43%, 37%,28% and31% in energy efficiency, spectral efficiency, outage probability for underserved users (OPOU), and domain CO₂ emissions against state-of-the-art baselines while satisfying corresponding URLLC guarantees crucial for different SDG-critical applications like precision agriculture, remote healthcare, smart grid management etc.
关键词
5G, Beyond-5G, Sustainable Development Goals, Deep Reinforcement Learning, Energy Harvesting, Network Slicing, Heterogeneous Networks, Proximal Policy Optimization, Spectral Efficiency, Green Communications, SDG Connectivity, Resource Optimization.
报告人
Dr Chellamuthu K
ASSOCIATE PROFESSOR Trichy；K.Ramakrishnan College of Engineering稿件作者
全部评论
重要日期
-
会议日期
11月20日
2026
至11月22日
2026
-
10月31日 2026
初稿截稿日期
-
11月07日 2026
提前注册日期
-
11月22日 2026
注册截止日期
主办单位
United Societies of Science
承办单位
Pondicherry University
协办单位
IEEE Section
IEEE Madras Section
IEEE Madras Section
联系方式
- ICon INDIA 2026
- ic******@usssociety.org
发表评论