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• W3046982562 abstract "Efficient resource allocation can maximize power efficiency, which is an important performance metric in future fifth-generation (5G) communications. The minimization of sum uplink power in order to enable green communications while concurrently fulfilling the strict demands of ultrareliability for short packets is an essential and central challenge that needs to be addressed in the design of 5G and subsequent wireless communication systems. To address this challenge, this article analyzes the joint optimization of various unmanned aerial vehicle (UAV) systems parameters, including the UAV’s position, height, beamwidth, and the resource allocation for uplink communications between ground Internet-of-Things (IoT) devices and a UAV employing short ultrareliable and low-latency (URLLC) data packets. Toward achieving the aforesaid task, we proposed a perturbation-based iterative optimization to minimize the sum uplink power in order to determine the optimal position for the UAV, its height, beamwidth of its antenna, and the blocklength allocated for each IoT device. It is shown that the proposed algorithm has lower time complexity, yields better performance than other benchmark algorithms, and achieves similar performance to exhaustive search. Moreover, the results also demonstrate that Shannon’s formula is not an optimum choice for modeling sum power for short packets as it can significantly underestimate the sum power, where our calculations show that there is an average difference of 47.51% for the given parameters between our proposed approach and Shannon’s formula. Finally, our results confirm that the proposed algorithm allows ultrahigh reliability for all the users and converges rapidly." @default.
• W3046982562 created "2020-08-10" @default.
• W3046982562 creator A5008261042 @default.
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• W3046982562 date "2021-02-01" @default.
• W3046982562 modified "2023-10-15" @default.
• W3046982562 title "Quasi-Optimization of Uplink Power for Enabling Green URLLC in Mobile UAV-Assisted IoT Networks: A Perturbation-Based Approach" @default.
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• W3046982562 doi "https://doi.org/10.1109/jiot.2020.3014039" @default.
• W3046982562 hasPublicationYear "2021" @default.
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