Joint Resource Allocation and Trajectory Design for Energy-Efficient UAV Assisted Networks With User Fairness Guarantee

Wang, Jing; Zhang, Haixia; Zhou, Xiaotian; Liu, Wenjie; Yuan, Dongfeng

doi:10.1109/jiot.2024.3386861

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2024

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Cited by 2 publications

References 53 publications

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Integrating AI-Driven Robust Control Algorithm with 3D Hand Gesture Recognition to Track an Underactuated Quadrotor Unmanned Aerial Vehicle (QUAV)

Al-Shayeb,

Abro,

Khan

et al. 2024

2024 IEEE 14th International Conference on Control System, Computing and Engineering (ICCSCE)

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Integrating AI-Driven Robust Control Algorithm with 3D Hand Gesture Recognition to Track an Underactuated Quadrotor Unmanned Aerial Vehicle (QUAV)

Al-Shayeb,

Abro,

Khan

et al. 2024

2024 IEEE 14th International Conference on Control System, Computing and Engineering (ICCSCE)

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A Comprehensive Review of Energy-Efficient Techniques for UAV-Assisted Industrial Wireless Networks

Zhang,

Zhao,

Mishra

et al. 2024

Energies

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The rapid expansion of the Industrial Internet-of-Things (IIoT) has spurred significant research interest due to the growth of security-aware, vehicular, and time-sensitive applications. Unmanned aerial vehicles (UAVs) are widely deployed within wireless communication systems to establish rapid and reliable links between users and devices, attributed to their high flexibility and maneuverability. Leveraging UAVs provides a promising solution to enhance communication system performance and effectiveness while overcoming the unprecedented challenges of stringent spectrum limitations and demanding data traffic. However, due to the dramatic increase in the number of vehicles and devices in the industrial wireless networks and limitations on UAVs’ battery storage and computing resources, the adoption of energy-efficient techniques is essential to ensure sustainable system implementation and to prolong the lifetime of the network. This paper provides a comprehensive review of various disruptive methodologies for addressing energy-efficient issues in UAV-assisted industrial wireless networks. We begin by introducing the background of recent research areas from different aspects, including security-enhanced industrial networks, industrial vehicular networks, machine learning for industrial communications, and time-sensitive networks. Our review identifies key challenges from an energy efficiency perspective and evaluates relevant techniques, including resource allocation, UAV trajectory design and wireless power transfer (WPT), across various applications and scenarios. This paper thoroughly discusses the features, strengths, weaknesses, and potential of existing works. Finally, we highlight open research issues and gaps and present promising potential directions for future investigation.

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Joint Resource Allocation and Trajectory Design for Energy-Efficient UAV Assisted Networks With User Fairness Guarantee

Cited by 2 publications

References 53 publications

Integrating AI-Driven Robust Control Algorithm with 3D Hand Gesture Recognition to Track an Underactuated Quadrotor Unmanned Aerial Vehicle (QUAV)

Integrating AI-Driven Robust Control Algorithm with 3D Hand Gesture Recognition to Track an Underactuated Quadrotor Unmanned Aerial Vehicle (QUAV)

A Comprehensive Review of Energy-Efficient Techniques for UAV-Assisted Industrial Wireless Networks

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