Spatio-Temporal Analysis of Spectrum Usage in Drone-based 5G eMBB Systems for Emergency Services

TL;DR

This paper analyzes how drone-based 5G connectivity for emergency services impacts existing 5G traffic, considering spatial, temporal, and event severity factors, using real-world data from London.

Contribution

It introduces a spatio-temporal analysis framework for emergency drone-based 5G links and assesses their effects on commercial 5G traffic.

Findings

Emergency drone links affect local 5G traffic patterns.

Event severity influences bandwidth allocation and network performance.

Spatial analysis reveals hotspots of network impact.

Abstract

The expectation for increased capabilities of 5G networks opens the way for new verticals to be developed, with a growing interest in providing 5G connectivity for emergency service support. In this paper we propose a drone-based deployment scenario, where multiple drones make up a wireless link to a 5G ground base station (BS), to provide connectivity to areas affected by emergency events. Assuming that a part of the BS's available bandwidth will be allocated to the emergency link in order to provide a high-speed and reliable connection, we present a spatio-temporal analysis of the effect of such a service on commercial 5G traffic, based on the locality, time of occurrence and severity of the event. Our work is based on recent advances in spatial analysis of BS locations, and extended datasets of emergency events in the area of greater London.