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- W4383113475 abstract "The ubiquitous deployment of Internet of Things (IoT) and the ever-evolving IoT services seek fully autonomous devices with no energy limitations. To fulfill this demand, we investigate the usage of unmanned aerial vehicles (UAV) to overcome the limited battery constraint of IoT deployments in hard-to-reach locations. Specifically, we present a UAV-enabled wake-up radio (WuR) and data collection (U-WuRIoT) solution for future IoT networks. The proposed solution leverages UAVs to wake-up IoT devices from an ultra-low power sleep mode by transmitting wake-up radio signals. Upon successful wake-up, the devices use their batteries to transmit the collected data to the UAV. In this article, we present an overview of U-WuRIoT and its applications and discuss the challenges and enabling technologies towards realizing it. Candidate enablers such as advances on wake-up receivers and UAV transmitters’ hardware, combined energy harvesting and WuR, new spectrum opportunities, energy beamforming, channel state information (CSI)-limited schemes, and UAV trajectory optimization are outlined. A realistic experimental testbed, using a fully-operational prototype implemented via off-the-shelf components, is constructed to validate the applicability of U-WuRIoT and its benefits compared to traditional duty cycling solutions. Furthermore, a theoretical study is conducted to extrapolate the performance of U-WuRIoT in large-scale deployments. The obtained experimental and theoretical results demonstrate that U-WuRIoT can extend the lifetime of the IoT device up to three times the lifetime when duty cycling is applied and can reduce the false alarm rate to less than 10%. Finally, key research directions toward implementing U-WuRIoT in the 6G era are identified." @default.
- W4383113475 created "2023-07-05" @default.
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- W4383113475 date "2023-01-01" @default.
- W4383113475 modified "2023-09-27" @default.
- W4383113475 title "Energy Conservative Data Aggregation for IoT Devices: An Aerial Wake-up Radio Approach" @default.
- W4383113475 doi "https://doi.org/10.1109/jiot.2023.3292305" @default.
- W4383113475 hasPublicationYear "2023" @default.
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