Joint Traffic and Obstacle-aware UAV Positioning Algorithm for Aerial Networks

TL;DR

This paper introduces TOPA, a UAV positioning algorithm that considers traffic demand and obstacles to optimize LoS connectivity, significantly improving network throughput in urban environments.

Contribution

The paper presents TOPA, a novel algorithm that jointly considers traffic and obstacle information for UAV placement, enhancing communication reliability and capacity.

Findings

Up to 100% increase in aggregate throughput

Significant improvement in network performance in obstacle-rich environments

Maintains fairness while optimizing throughput

Abstract

Unmanned Aerial Vehicles (UAVs) are increasingly used as cost-effective and flexible Wi-Fi Access Points (APs) and cellular Base Stations (BSs) to enhance Quality of Service (QoS). In disaster management scenarios, UAV-based networks provide on-demand wireless connectivity when traditional infrastructures fail. In obstacle-rich environments like urban areas, reliable high-capacity communications links depend on Line-of-Sight (LoS) availability, especially at higher frequencies. Positioning UAVs to consider obstacles and enable LoS communications represents a promising solution that requires further exploration and development. The main contribution of this paper is the Traffic- and Obstacle-aware UAV Positioning Algorithm (TOPA). TOPA takes into account the users' traffic demand and the need for LoS between the UAV and the ground users in the presence of obstacles. The network performance achieved when using TOPA was evaluated through ns-3 simulations. The results show up to 100% improvement in the aggregate throughput without compromising fairness.