# Ray Tracing Analysis for UAV-assisted Integrated Access and Backhaul Millimeter Wave Networks

## TL;DR

This paper investigates how UAVs can enhance mmWave cellular networks by acting as relays, using ray tracing simulations to analyze coverage improvements and propose adaptive power strategies for better signal quality.

## Contribution

It introduces a ray tracing-based analysis of UAV-assisted mmWave networks, implementing relaying mechanisms and adaptive power control to improve coverage and signal quality.

## Key findings

- UAV relays significantly improve coverage in mmWave bands.
- Decode-and-forward relaying outperforms amplify-and-forward in coverage.
- Adaptive power control enhances SINR and network performance.

## Abstract

The use of Millimeter-wave (mmWave) spectrum in cellular communications has recently attracted growing interest to support the expected massive increase in traffic demands. However, the high path-loss at mmWave frequencies poses severe challenges. In this paper, we analyze the potential coverage gains of using unmanned aerial vehicles (UAVs), as hovering relays, in integrated access and backhaul (IAB) mmWave cellular scenarios. Specifically, we utilize the WinProp software package, which employs ray tracing methodology, to study the propagation characteristics of outdoor mmWave channels at 30 and 60 GHz frequency bands in a Manhattan-like environment. In doing so, we propose the implementation of amplify-and-forward (AF) and decode-and-forward (DF) relaying mechanisms in the WinProp software. We show how the 3D deployment of UAVs can be defined based on the coverage ray tracing maps at access and backhaul links. Furthermore, we propose an adaptive UAV transmission power for the AF relaying. We demonstrate, with the aid of ray tracing simulations, the performance gains of the proposed relaying modes in terms of downlink coverage, and the received signal to interference and noise ratio (SINR).