2022
DOI: 10.1155/2022/8805416
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Deep Reinforcement Learning-Based UAV Data Collection and Offloading in NOMA-Enabled Marine IoT Systems

Abstract: The rapid growth of maritime wireless communication demand and the complex offshore wireless communication environment have brought challenges to ensure the real-time and reliability of data transmission in the marine Internet of Things (MIoT). Unmanned aerial vehicles (UAVs) have great advantages in enhancing coverage and channel quality. Hence, we investigate a UAV-assisted data collection and data offloading system based on nonorthogonal multiple access (NOMA) technology in this paper. We jointly optimize t… Show more

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Cited by 2 publications
(2 citation statements)
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“…The simulation results indicated a significantly reduction of the computation tasks overall execution time. In [108], a UAV-assisted data collection and data offloading system in marine IoT has been investigated. The objective is to minimize the total mission completion time, by taking into account UAV trajectory, data offloading capabilities, buoy-UAV association, and the transmit power.…”
Section: B Data Offloadingmentioning
confidence: 99%
“…The simulation results indicated a significantly reduction of the computation tasks overall execution time. In [108], a UAV-assisted data collection and data offloading system in marine IoT has been investigated. The objective is to minimize the total mission completion time, by taking into account UAV trajectory, data offloading capabilities, buoy-UAV association, and the transmit power.…”
Section: B Data Offloadingmentioning
confidence: 99%
“…Shortly, a general framework combining MIMO and NOMA has been constructed [29]. As the power domain is unrelated to the domains of time, frequency, and code, NOMA is compatible with most conventional methods to deliver multiple benefits simultaneously, like the NOMA-based power transfer and backscatter communication in [30], the NOMA-based mobile edge computing (MEC) in [31], and the NOMAassisted UAV system in [32]. In PD-NOMA, successive interference cancellation (SIC) is the key component for decoding.…”
Section: Introductionmentioning
confidence: 99%