Empowering Rural Areas with Multi-radio Microwave Backhaul Supported by Digital Twin for 5G IAB-based FWA

2026-07-23

AI Summary

This study addresses the low energy efficiency of multi-hop backhaul networks in rural 5G fixed wireless access (FWA) deployments. To tackle this challenge, the authors propose a novel multi-hop architecture that integrates long-range microwave links, 5G integrated access and backhaul (IAB), and FWA. For the first time, a digital twin-driven dynamic radio-frequency management mechanism is introduced to intelligently control the activation and sleep states of microwave backhaul units based on real-time traffic load. The energy-efficiency optimization problem within the digital twin is solved using deep Q-learning, which collaborates with conventional optimizers to jointly manage the physical network, thereby achieving synergistic optimization of capacity and energy savings. Simulation results demonstrate that the proposed approach significantly reduces overall backhaul energy consumption while meeting user rate requirements.

Abstract

For digital inclusion, high-capacity Internet access should be provided to rural areas to support a range of services and applications. Due to the high operating costs of fiber-optic deployment, Fixed Wireless Access (FWA) is becoming a more attractive internet solution for rural areas. However, 5G FWA is a one-hop solution with limited coverage. A multi-hop solution is needed for wider rural coverage. This work considers a unified solution combining long-haul microwave, 5G Integrated Access and Backhaul (IAB), and FWA to provide a multi-hop network for extended coverage and high network capacity in rural areas. A key challenge for such a network is that energy consumption increases with the number of hops, a problem that has been overlooked in the existing literature. To address this, we propose energy-efficiency microwave backhaul for IAB-based FWA as the Physical Twin (PT). We develop an energy-efficient strategy to optimize radio start-up, serving, sleeping, and wake-up states for microwave backhaul connecting 5G IAB-based FWA serving rural areas. By operating the network at reduced capacity during low utilization, we aim to minimize energy consumption. Then, we present a Digital Twin (DT) of PT to improve its performance. We solve the formulated optimization problem using deep Q-learning in DT and the optimization solver in PT. The simulation results show that our approach satisfies the data rate requirements while reducing energy consumption.

Problem

• 5G IAB
• Fixed Wireless Access
• Microwave Backhaul
• Energy Efficiency
• Rural Coverage

Innovation

• Digital Twin
• Energy Efficiency
• Microwave Backhaul
• 5G IAB
• Multi-hop FWA