Sustaining Dynamic Traffic in Dense Urban Areas with High Altitude Platform Stations (HAPS)

TL;DR

This paper explores how high altitude platform stations (HAPS) can supplement traditional radio access networks to efficiently manage unpredictable and dense urban mobile traffic while reducing energy consumption.

Contribution

It introduces the concept of using HAPS super macro base stations to complement RANs, demonstrating their potential for energy-efficient handling of dynamic urban traffic.

Findings

HAPS-SMBSs can effectively handle peak traffic in dense urban areas.

HAPS complement RANs by reducing energy consumption and over-provisioning.

Simulation results show improved sustainability with HAPS deployment.

Abstract

The impact of information and communication technologies on global energy consumption is increasing every year, and mobile networks account for a significant portion of it. More than 50% of the total energy consumption of mobile networks is issued from radio access networks (RANs), due mainly to the rapid penetration of data-intensive applications and the increasing heterogeneity, dynamicity, and unpredictability of traffic. To tackle these high-demanding problems, RAN densification through the installation of additional base stations in high-demand areas is conventionally used. However, this leads to inefficient energy use and over-provisioning issues. In this context, high altitude platform stations (HAPS) may be used to complement RANs and sustain their services in densely populated areas, where traffic can peak unpredictably. Due to their wide coverage areas, substantial communication payloads, and green energy model, HAPS super macro base stations (SMBSs) are capable of handling the massive and dynamic mobile data traffic of ground users. In this paper, we show how HAPS-SMBSs can complement RANs and serve the dynamic and unpredictable traffic demands of users in an energy-efficient manner. Through the simulation of a case study, we demonstrate the performance of a HAPS-SMBS compared to the conventional RAN densification method and analyze the two approaches in terms of sustainability.