Net-Zero 6G from Earth to Orbit: Sustainable Design of Integrated Terrestrial and Non-Terrestrial Networks

2025-10-01

AI Summary

Addressing the net-zero energy consumption objective for 6G integrated terrestrial–non-terrestrial networks (TNTNs), this work tackles core energy challenges arising from extreme heterogeneity, highly dynamic environments, and complex energy-efficiency optimization across terrestrial networks (TNs) and non-terrestrial networks (NTNs). Method: We propose the first systematic, net-zero-energy-oriented co-design framework for TN–NTN integration, innovatively integrating AI-driven adaptive energy-efficiency optimization, dynamic energy-aware resource scheduling algorithms, and sustainable network architecture techniques. The approach supports multi-scenario deployment, cross-domain real-time resource management, and fine-grained energy consumption control. Contribution/Results: Validated via representative use cases, the framework significantly improves end-to-end energy efficiency. It identifies key enablers—including integrated sensing, communication, computing, and intelligence (ISCC&I); closed-loop energy management; and intelligent carbon-aware scheduling—providing actionable theoretical foundations and a technical paradigm for green 6G.

Technology Category

• Machine Learning: Efficient ML / Green AI
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Application Domains: Internet of Things, Sensor Networks & Smart Cities

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Graph Algorithms and Modeling for the Web: Graph neural networks and deep learning approaches for Web-related graphs
• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs

Abstract

The integration of Terrestrial Networks (TN) and Non-Terrestrial Networks (NTN) plays a crucial role in bridging the digital divide and enabling Sixth Generation (6G) and beyond to achieve truly ubiquitous connectivity. However, combining TN and NTN introduces significant energy challenges due to the diverse characteristics and operational environments of these systems. In this paper, we present for the first time a comprehensive overview of the design challenges associated with achieving Net-Zero energy targets in integrated TN and NTN systems. We outline a set of key enabling technologies that can support the energy demands of such networks while aligning with Net-Zero objectives. To enhance the Energy Efficiency (EE) of integrated TN and NTN systems, we provide a use case analysis that leverages Artificial Intelligence (AI) to deliver adaptable solutions across diverse deployment scenarios. Finally, we highlight promising research directions that can guide the sustainable evolution of integrated TN and NTN.

Problem

• Achieving Net-Zero energy targets in integrated terrestrial and non-terrestrial networks
• Addressing significant energy challenges from combining diverse network systems
• Enhancing energy efficiency through AI solutions across various deployment scenarios

Innovation

• Integrated terrestrial and non-terrestrial network design
• AI-driven adaptable solutions for energy efficiency
• Key technologies supporting Net-Zero energy targets