Edge Computing and Wireless Power Transfer for Integrated Radar and Communication-Equipped IoT Systems

In this letter, we investigate the wireless power-enabled mobile edge computing (WP-MEC) for an integrated radar and communication (IRC)-equipped Internet of Things (IoT) system. The system allows an IoT device to harvest energy from a power station (PS) and offload its computation task to the PS. F...

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Bibliographic Details
Published in:IEEE wireless communications letters 2024-09, Vol.13 (9), p.2457-2461
Main Authors: Le, Hung Hoang, Long, Nguyen Hoang Khanh, Luong, Nguyen Cong, Hoa, Nguyen Tien, Nam, Tran Xuan, Kim, Dong In
Format: Article
Language:English
Subjects:
advantage actor critic
Algorithms
Computation offloading
Computing time
Edge computing
Energy harvesting
Energy transfer
Integrated radar and communication
Internet of Things
Machine learning
Mobile computing
OFDM
Orthogonal Frequency Division Multiplexing
Performance evaluation
Power plants
Radar
Radar tracking
Servers
Task analysis
Tracking devices
Wireless communication
Wireless communications
wireless power transfer
Wireless power transmission
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Summary:In this letter, we investigate the wireless power-enabled mobile edge computing (WP-MEC) for an integrated radar and communication (IRC)-equipped Internet of Things (IoT) system. The system allows an IoT device to harvest energy from a power station (PS) and offload its computation task to the PS. Furthermore, the system enables the IoT device to leverage the offloading bits for the radar tracking. Orthogonal frequency division multiplexing (OFDM) technique is used for the task offloading of the IoT devices. We aim to maximize computation efficiency over the IoT devices subject to their radar performance requirements by optimizing the energy transfer time, the OFDM subcarrier allocation to the devices, and the transmit power. Due to the stochastic and dynamic nature of the computing resource and the targets, we leverage a deep reinforcement learning (DRL) algorithm, namely Advantage Actor Critic (A2C), to solve the problem. Simulation results are provided to evaluate the effectiveness and improvement of the A2C algorithm.
ISSN:2162-2337
2162-2345
DOI:10.1109/LWC.2024.3418928