Energy-efficient drone trajectory planning for the localization of 6G-enabled IoT devices

Sahar Kouroshnezhad, Ali Peiravi, Mohammad Sayad Haghighi*, Alireza Jolfaei

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

24 Citations (Scopus)

Abstract

6G will be an enabler for the massive Internet of Things (IoT) in which millions of devices communicate at high data rates and low latencies. One key area among 6G applications is advanced sensing. However, higher speed implies moving to higher frequencies, which generally require more transmission power. In remote sensing, this causes problems, since either we have to increase the number of sensors and lower their communications ranges or increase their ranges and accept faster battery depletion. To cut the cost, even localization modules are not usually included in sensors. However, in many applications, IoT sensors must know their locations. Recent advances in the field of drones have led to promising solutions for localization. In this article, we propose a novel approach called semidynamic mobile anchor guiding (SEDMAG) for drones which aims at energy-conservative trajectory planning and localization of massive IoT devices. In this approach, the drone tracks the shortest path over a connected graph. This path determines the visiting order of devices. But we show that the complexity of this approach is high, thus, a graph reduction approach is proposed. It reduces the complexity and decreases the drones' energy consumption and positioning delay. The drone then follows a weighted search algorithm (WSA) to dynamically visit the devices. Simulation results are used to verify the superiority of the proposed approach.

Original languageEnglish
Pages (from-to)5202-5210
Number of pages9
JournalIEEE Internet of Things Journal
Volume8
Issue number7
Early online date20 Oct 2020
DOIs
Publication statusPublished - 1 Apr 2021

Keywords

  • 6G
  • advanced sensors
  • drone
  • dynamic path planning
  • energy efficiency
  • Internet of Things (IoT)
  • localization

Fingerprint

Dive into the research topics of 'Energy-efficient drone trajectory planning for the localization of 6G-enabled IoT devices'. Together they form a unique fingerprint.

Cite this