Impact of Channel Estimation Feedback on 5G NR Integrated Access and Backhaul

Integrated Access and Backhaul (IAB) systems are gaining more and more interest for future wireless networks. IAB combines the access and the backhaul links to improve network efficiency and reduce deployment costs. This study investigates the impact of the channel estimation feedback on digital precoding in 5G NR Mixed Numerology IAB systems. Combining analog beamforming with Reconfigurable Intelligent Surface (RIS) and digital precoding, we address challenges related to inter-user and inter-numerology interference. We rely on the model of an existing RIS and on realistic channel modeling. We demonstrate the effectiveness of hybrid precoding in interference mitigation, enhancing system performance with limited complexity. Simulation results affirm the potential of our approach for high-capacity and interference-resilient wireless networks, offering valuable insights for future designs.

I. Introduction

The deployment of 5G networks introduces new paradigms and challenges, particularly in the context of Integrated Access and Backhaul (IAB) [1]. IAB combines both access and backhaul functionalities in a unified framework, offering a cost-effective and efficient approach for the deployment of next-generation wireless networks. This integration enhances network reliability, flexibility, and scalability, supporting diverse services and applications with varying quality of service requirements.