Energy Efficient Altitude Optimization of an Aerial Access Point

TL;DR

This paper develops an energy-efficient altitude optimization method for aerial access points serving ground users, incorporating the vehicle's energy consumption into the model and ensuring global optimality.

Contribution

It introduces a novel optimization framework that accounts for aerial vehicle energy use and compares sequential convex programming with a global optimization method.

Findings

SCP solution matches the global optimum from MFP.

Energy consumption significantly influences optimal altitude.

Numerical results validate the proposed optimization approach.

Abstract

In this paper, we propose an energy-efficient optimal altitude for an aerial access point (AAP), which acts as a flying base station to serve a set of ground user equipment (UE). Since the ratio of total energy consumed by the aerial vehicle to the communication energy is very large, we include the aerial vehicle's energy consumption in the problem formulation. After considering the energy consumption model of the aerial vehicle, our objective is translated into a non-convex optimization problem of maximizing the global energy efficiency (GEE) of the aerial communication system, subject to altitude and minimum individual data rate constraints. At first, the non-convex fractional objective function is solved by using sequential convex programming (SCP) optimization technique. To compare the result of SCP with the global optimum of the problem, we reformulate the initial problem as a monotonic fractional optimization problem (MFP) and solve it using the polyblock outer approximation (PA) algorithm. Numerical results show that the candidate solution obtained from SCP is the same as the global optimum found using the monotonic fractional programming technique. Furthermore, the impact of the aerial vehicle's energy consumption on the optimal altitude determination is also studied.