UAV-Assisted Heterogeneous Networks for Capacity Enhancement

Vishal Sharma, Mehdi Bennis, Rajesh Kumar

Research output: Contribution to journalArticlepeer-review

277 Citations (Scopus)

Abstract

Modern day wireless networks have tremendously evolved driven by a sharp increase in user demands, continuously requesting more data and services. This puts significant strain on infrastructure-based macro cellular networks due to the inefficiency in handling these traffic demands, cost effectively. A viable solution is the use of unmanned aerial vehicles (UAVs) as intermediate aerial nodes between the macro and small cell tiers for improving coverage and boosting capacity. This letter investigates the problem of user-demand-based UAV assignment over geographical areas subject to high traffic demands. A neural-based cost function approach is formulated, in which UAVs are matched to a particular geographical area. It is shown that leveraging multiple UAVs not only provides long-range connectivity but also better load balancing and traffic offload. Simulation study demonstrates that the proposed approach yields significant improvements in terms of fifth percentile spectral efficiency up to 38% and reduced delays up to 37.5% compared with a ground-based network baseline without UAVs.

Original languageEnglish
Pages (from-to)1207-1210
Number of pages4
JournalIEEE Communications Letters
Volume20
Issue number6
Early online date12 Apr 2016
DOIs
Publication statusPublished - Jun 2016
Externally publishedYes

Keywords

  • 5G
  • interference coordination
  • quadcopter
  • UAVs
  • unmanned aerial base stations

ASJC Scopus subject areas

  • Modelling and Simulation
  • Computer Science Applications
  • Electrical and Electronic Engineering

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