Power-efficient wireless coverage using minimum number of uavs

Ahmad Sawalmeh, Noor Shamsiah Othman, Guanxiong Liu, Abdallah Khreishah, Ali Alenezi, Abdulaziz Alanazi

Research output: Contribution to journalArticlepeer-review

Abstract

Unmanned aerial vehicles (UAVs) can be deployed as backup aerial base stations due to cellular outage either during or post natural disaster. In this paper, an approach involving multiUAV three-dimensional (3D) deployment with power-efficient planning was proposed with the objective of minimizing the number of UAVs used to provide wireless coverage to all outdoor and indoor users that minimizes the required UAV transmit power and satisfies users’ required data rate. More specifically, the proposed algorithm iteratively invoked a clustering algorithm and an efficient UAV 3D placement algorithm, which aimed for maximum wireless coverage using the minimum number of UAVs while minimizing the required UAV transmit power. Two scenarios where users are uniformly and non-uniformly distributed were considered. The proposed algorithm that employed a Particle Swarm Optimization (PSO)-based clustering algorithm resulted in a lower number of UAVs needed to serve all users compared with that when a K-means clustering algorithm was employed. Furthermore, the proposed algorithm that iteratively invoked a PSO-based clustering algorithm and PSO-based efficient UAV 3D placement algorithms reduced the execution time by a factor of ≈1/17 and ≈1/79, respectively, compared to that when the Genetic Algorithm (GA)-based and Artificial Bees Colony (ABC)-based efficient UAV 3D placement algorithms were employed. For the uniform distribution scenario, it was observed that the proposed algorithm required six UAVs to ensure 100% user coverage, whilst the benchmarker algorithm that utilized Circle Packing Theory (CPT) required five UAVs but at the expense of 67% of coverage density.

Original languageEnglish (US)
Article number223
JournalSensors
Volume22
Issue number1
DOIs
StatePublished - Jan 1 2022

ASJC Scopus subject areas

  • Analytical Chemistry
  • Information Systems
  • Atomic and Molecular Physics, and Optics
  • Biochemistry
  • Instrumentation
  • Electrical and Electronic Engineering

Keywords

  • Artificial bees colony (ABC)
  • Efficient 3D placement
  • Genetic algorithm (GA)
  • K-means
  • Particle swarm optimization (PSO)
  • Unmanned aerial vehicles (UAVs)

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