Positioning of Multiple Unmanned Aerial Vehicle Base Stations in future Wireless Network

TL;DR

This paper proposes a novel algorithm for optimal 3D placement of multiple UAV base stations in mmWave networks to ensure coverage and quality of service, considering various operational constraints.

Contribution

It introduces a suboptimal algorithm that approximates an NP-hard 3D positioning problem for UAV-BSs using l_1-norm minimization, enabling feasible deployment solutions.

Findings

Algorithm achieves feasible UAV-BS deployment locations.

Satisfies SINR, altitude, and zone constraints.

Addresses NP-hardness with l_1 approximation.

Abstract

Unmanned aerial vehicle (UAV) base stations (BSs) are reliable and efficient alternative to full fill the coverage and capacity requirements when the backbone network fails to provide such requirements due to disasters. In this paper, we consider optimal UAV-deployment problem in 3D space for a mmWave network. The objective is to deploy multiple aerial BSs simultaneously to completely serve the ground users. We develop a novel algorithm to find the feasible positions for a set of UAV-BSs from a predefined set of locations, subject to a signal-to-interference-plus-noise ratio (SINR) constraint of every associated user, UAV-BS's limited hovering altitude constraint and restricted operating zone constraint. We cast this 3D positioning problem as an l_0 minimization problem. This is a combinatorial, NP-hard problem. We approximate the l_0 minimization problem as non-combinatorial l_1-norm problem. Therefore, we provide a suboptimal algorithm to find a set of feasible locations for the UAV-BSs to operate. The analysis shows that the proposed algorithm achieves a set of the location to deploy multiple UVA-BSs simultaneously while satisfying the constraints.