Aerial Base Station Placement via Propagation Radio Maps

TL;DR

This paper proposes a novel method using propagation radio maps and convex optimization to optimally place aerial base stations for improved coverage, considering complex air-to-ground channels and operational constraints.

Contribution

It introduces a radio map-based approach combined with convex relaxation and ADMM for efficient ABS placement considering realistic channel models and constraints.

Findings

Method outperforms conventional placement strategies.

Solver scales linearly with number of ground terminals.

Analytical convergence proof provided.

Abstract

The deployment of aerial base stations (ABSs) on unmanned aerial vehicles (UAVs) presents a promising solution for extending cellular connectivity to areas where terrestrial infrastructure is overloaded, damaged, or absent. A pivotal challenge in this domain is to decide the locations of a set of ABSs to effectively serve ground-based users. Most existing approaches oversimplify this problem by assuming that the channel gain between two points is a function of solely distance and, sometimes, also the elevation angle. In turn, this paper leverages propagation radio maps to account for arbitrary air-to-ground channel gains. This methodology enables the identification of an approximately minimal set of locations where ABSs need to be deployed to ensure that all ground terminals achieve a target service rate, while adhering to backhaul capacity limitations and avoiding designated no-fly zones. Relying on a convex relaxation technique and the alternating direction method of multipliers (ADMM), this paper puts forth a solver whose computational complexity scales linearly with the number of ground terminals. Convergence is established analytically and an extensive set of simulations corroborate the merits of the proposed scheme relative to conventional methods.