University of Oulu

O. Martínez Rosabal, O. L. A. López, D. E. Pérez, M. Shehab, H. Hilleshein and H. Alves, "Minimization of the Worst Case Average Energy Consumption in UAV-Assisted IoT Networks," in IEEE Internet of Things Journal, vol. 9, no. 17, pp. 15827-15838, 1 Sept.1, 2022, doi: 10.1109/JIOT.2022.3150419.

Minimization of the worst-case average energy consumption in UAV-assisted IoT networks

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Author: Rosabal, Osmel Martínez1; López, Onel Alcaraz1; Pérez, Dian Echevarría1;
Organizations: 1Centre for Wireless Communications (CWC), University of Oulu, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 1.6 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2022
Publish Date: 2022-09-07


The Internet of Things (IoT) brings connectivity to a massive number of devices that demand energy-efficient solutions to deal with limited battery capacities, uplink-dominant traffic, and channel impairments. In this work, we explore the use of Unmanned Aerial Vehicles (UAVs) equipped with configurable antennas as a flexible solution for serving low-power IoT networks. We formulate an optimization problem to set the position and antenna beamwidth of the UAV, and the transmit power of the IoT devices subject to average-Signal-to-average-Interference-plus-Noise Ratio (S̄INR) Quality of Service (QoS) constraints. We minimize the worst-case average energy consumption of the latter, thus, targeting the fairest allocation of the energy resources. The problem is non-convex and highly non-linear; therefore, we re-formulate it as a series of three geometric programs that can be solved iteratively. Results reveal the benefits of planning the network compared to a random deployment in terms of reducing the worst-case average energy consumption. Furthermore, we show that the target S̄INR is limited by the number of IoT devices, and highlight the dominant impact of the UAV hovering height when serving wider areas. Our proposed algorithm outperforms other optimization benchmarks in terms of minimizing the average energy consumption at the most energy-demanding IoT device, and convergence time.

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Series: IEEE internet of things journal
ISSN: 2372-2541
ISSN-E: 2327-4662
ISSN-L: 2327-4662
Volume: 9
Issue: 17
Pages: 15827 - 15838
DOI: 10.1109/JIOT.2022.3150419
Type of Publication: A1 Journal article – refereed
Field of Science: 213 Electronic, automation and communications engineering, electronics
Funding: This work is partially supported by Academy of Finland 6Genesis Flagship (Grant no. 318927)
Academy of Finland Grant Number: 318927
Detailed Information: 318927 (Academy of Finland Funding decision)
Copyright information: © 2022 The Authors. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see