3-D Dynamic UAV Base Station Location Problem

TL;DR

This paper addresses the complex problem of dynamically positioning a UAV-based communication station over time to maximize coverage, introducing new formulations and solution methods including a non-linear programming model, a Lagrangean Decomposition Algorithm, and a Continuum Approximation model.

Contribution

It develops novel formulations and solution approaches for the 3-D dynamic UAV base station location problem, addressing non-convexity and computational challenges.

Findings

CA model offers efficient solutions with good accuracy

LDA helps in solving large-scale problems

Numerical results validate the effectiveness of the models

Abstract

We address a dynamic covering location problem of an Unmanned Aerial Vehicle Base Station (UAV-BS), where the location sequence of a single UAV-BS in a wireless communication network is determined to satisfy data demand arising from ground users. This problem is especially relevant in the context of smart grid and disaster relief. The vertical movement ability of the UAV-BS and non-convex covering functions in wireless communication restrict utilizing classical planar covering location approaches. Therefore, we develop new formulations to this emerging problem for a finite time horizon to maximize the total coverage. In particular, we develop a mixed-integer non-linear programming formulation which is non-convex in nature, and propose a Lagrangean Decomposition Algorithm (LDA) to solve this formulation. Due to high complexity of the problem, the LDA is still unable to find good local solutions to large-scale problems. Therefore, we develop a Continuum Approximation (CA) model and show that CA would be a promising approach in terms of both computational time and solution accuracy. Our numerical study also shows that the CA model can be a remedy to build efficient initial solutions for exact solution algorithms.