pith. sign in

arxiv: 1603.00300 · v1 · pith:NFVLSRZKnew · submitted 2016-02-26 · 🧮 math.OC · cs.NI

Efficient 3-D Placement of an Aerial Base Station in Next Generation Cellular Networks

classification 🧮 math.OC cs.NI
keywords placementbasedrone-cellsproblemstationsaerialcellularefficient
0
0 comments X
read the original abstract

Agility and resilience requirements of future cellular networks may not be fully satisfied by terrestrial base stations in cases of unexpected or temporary events. A promising solution is assisting the cellular network via low-altitude unmanned aerial vehicles equipped with base stations, i.e., drone-cells. Although drone-cells provide a quick deployment opportunity as aerial base stations, efficient placement becomes one of the key issues. In addition to mobility of the drone-cells in the vertical dimension as well as the horizontal dimension, the differences between the air-to-ground and terrestrial channels cause the placement of the drone-cells to diverge from placement of terrestrial base stations. In this paper, we first highlight the properties of the dronecell placement problem, and formulate it as a 3-D placement problem with the objective of maximizing the revenue of the network. After some mathematical manipulations, we formulate an equivalent quadratically-constrained mixed integer non-linear optimization problem and propose a computationally efficient numerical solution for this problem. We verify our analytical derivations with numerical simulations and enrich them with discussions which could serve as guidelines for researchers, mobile network operators, and policy makers.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. On the Performance of Renewable Energy-Powered UAV-Assisted Wireless Communications

    cs.NI 2019-07 unverdicted novelty 5.0

    Derives closed-form PDFs, CDFs, and MGFs for harvested solar/wind power, computes energy and SNR outage probabilities via Gil-Pelaez inversion, and obtains closed-form solutions for UAV transmit power and flight time ...