Integrated resource and trajectory optimization for IoT-enabled multi-UAV wireless powered communication networks

In this paper, we investigate a multi-UAV wireless powered communication (WPC) system for Internet of Things (IoT) networks where multiple unmanned aerial vehicles (UAVs) act as centrally co-optimized aerial platforms to provide on-demand wireless connectivity in areas lacking terrestrial infrastructure. By partitioning each communication time slot into distinct downlink and uplink phases, the UAVs first wirelessly transfer energy to IoT devices, which subsequently utilize the harvested energy for uplink data transmission. We formulate an optimization problem that maximizes the minimum average data rate among all users, thereby ensuring fairness. This is achieved by jointly optimising UAV–user associations, subslot time allocations, user transmit powers, and multi-UAV trajectories. To address the resulting large-scale mixed-integer non-convex problem, we propose an efficient iterative algorithm based on block coordinate descent (BCD) and successive convex approximation (SCA). Numerical results validate the efficacy of the proposed scheme, demonstrating significant gains in user fairness and system throughput compared with several benchmark approaches.

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Publication Details

Journal
Journal of Information and Telecommunication
Published
2026-07-30
DOI
https://doi.org/10.1080/24751839.2026.2708456
Primary Topic
UAV Applications and Optimization
Type
article
Field-Weighted Citation Impact
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article

Integrated resource and trajectory optimization for IoT-enabled multi-UAV wireless powered communication networks

Muheeb Ahmed, Stuart Nicholson, Kayode Popoola, Srilatha Narayanagari et al.
Journal of Information and Telecommunication
UAV Applications and Optimization
article

Integrated resource and trajectory optimization for IoT-enabled multi-UAV wireless powered communication networks

Muheeb Ahmed, Stuart Nicholson, Kayode Popoola, Srilatha Narayanagari, Ayodeji Ajani
article en

Abstract

In this paper, we investigate a multi-UAV wireless powered communication (WPC) system for Internet of Things (IoT) networks where multiple unmanned aerial vehicles (UAVs) act as centrally co-optimized aerial platforms to provide on-demand wireless connectivity in areas lacking terrestrial infrastructure. By partitioning each communication time slot into distinct downlink and uplink phases, the UAVs first wirelessly transfer energy to IoT devices, which subsequently utilize the harvested energy for uplink data transmission. We formulate an optimization problem that maximizes the minimum average data rate among all users, thereby ensuring fairness. This is achieved by jointly optimising UAV–user associations, subslot time allocations, user transmit powers, and multi-UAV trajectories. To address the resulting large-scale mixed-integer non-convex problem, we propose an efficient iterative algorithm based on block coordinate descent (BCD) and successive convex approximation (SCA). Numerical results validate the efficacy of the proposed scheme, demonstrating significant gains in user fairness and system throughput compared with several benchmark approaches.

Journal of Information and Telecommunication
Greater Manchester Police (GB), University of Manchester (GB), Vysoká Škola Realitní Institut Franka Dysona (CZ), Institute of Engineering (NP)
Industry, innovation and infrastructure
Openalex Percentile: Top 5%
UAV Applications and Optimization
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