Capacity and Energy Trade-Offs in FR3 6G Networks Using Real Deployment Data

2026-01-20

AI Summary

This study addresses the trade-off between capacity enhancement and increased energy consumption in 6G deployments within the FR3 band (7–24 GHz) by proposing a non-co-located, user hotspot-oriented deployment strategy. Leveraging real-world 4G/5G base station locations and traffic data from China, the authors develop Giulia—a deployment-aware system-level simulation framework that departs from conventional 3GPP templates—to jointly evaluate the energy efficiency and capacity of multi-layer 6G networks. Results demonstrate that, compared to traditional co-located approaches, the proposed strategy achieves up to a 9.5× improvement in median throughput while avoiding 59% of additional energy consumption, thereby substantially enhancing throughput-per-watt efficiency. This work provides empirical evidence and a novel paradigm for green and high-performance 6G network deployment.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Sampling/Simulation-based Search
• Machine Learning: Efficient ML / Green AI

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

This article presents a data-driven system-level analysis of multi-layer 6G networks operating in the upper mid-band (FR3: 7-24 GHz). Unlike most prior studies based on 3rd Generation Partnership Project (3GPP) templates, we leverage real-world deployment and traffic data from a commercial 4G/5G network in China to evaluate practical 6G strategies. Using Giulia-a deployment-informed system-level heterogeneous network model-we show that 6G can boost median throughput by up to 9.5x over heterogeneous 4G+5G deployments, but also increases power usage by up to 59%. Critically, co-locating 6G with existing sites delivers limited gains while incurring high energy cost. In contrast, non-co-located, traffic-aware deployments achieve superior throughput-to-watt efficiency, highlighting the need for strategic, user equipment (UE) hotspot-focused 6G planning.

Problem

• capacity-energy trade-off
• 6G networks
• FR3
• deployment strategy
• energy efficiency

Innovation

• data-driven
• FR3 6G
• non-co-located deployment
• throughput-to-watt efficiency
• heterogeneous network modeling