Empirical Line-of-Sight Probability Modeling for UAVs in Random Urban Layouts

TL;DR

This paper introduces the Urban LoS Simulator (ULS) to empirically model the probability of line-of-sight for UAVs in various random urban layouts, highlighting limitations of traditional Manhattan grid models for real-world urban environments.

Contribution

It presents a novel empirical PLoS modeling approach using ULS for random city layouts, improving accuracy over simplified grid-based models.

Findings

ULS effectively models PLoS in diverse urban layouts.

Manhattan grid models may not accurately reflect real-world PLoS.

Insights into the applicability of simplified models for urban UAV communication.

Abstract

Accurate Probability of Line-of-Sight (PLoS) modeling is important in evaluating the performance of Unmanned Aerial Vehicle (UAV)-based communication systems in urban environments, where real-time communication and low latency are often major requirements. Existing PLoS models often rely on simplified Manhattan grid layouts using International Telecommunication Union (ITU)-defined built-up parameters, which may not reflect the randomness of real cities. Therefore, this paper introduces the Urban LoS Simulator (ULS) to model PLoS for three random city layouts with varying building sizes and shapes constructed using ITU built-up parameters. Based on the ULS simulated data, we obtained the empirical PLoS for four standard urban environments across three different city layouts. Finally, we analyze how well Manhattan grid-based models replicate PLoS results from random and real-world layouts, providing insights into their applicability for time-critical communication systems in urban IoT networks.