Communications

Resource Efficient Real-Time Reliability Model for Multi-Agent IoT Systems

Resource Efficient Real-Time Reliability Model for Multi-Agent IoT Systems is called ERT-CORE. It defines specific input parameters, i.e., system's workload, average request processing time and availability. Defined parameters reflect system's state and react on its changes. Based on these parameters system reliability evaluation is performed.

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This is the simulation results for the submitted manuscript entitled "Enhancing transmission efficiency of mega-constellation LEO satellite networks".

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Based on CPU and GPU platforms, the phase detection algorithm based on GPU has been verified by measured data for several times, and the phase detection results are obtained.

 

The datasets are some of the main phase value information of each baseline of the rotating phase interferometer before and after gPU-based FX cross-correlation algorithm.

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For the innovation challenge for unmanned aerial vehicle (UAV) communications, we propose to demonstrate a two-tier Low Power Wide Area Network (LP-WAN) based on UAV base stations suitable for dynamic deployment and reconfiguration in deep rural areas. The proposed UAV-based LP-WAN network augments the existing macro-cellular NB-IoT network (Tier 1) with either an additional layer of mobile NB-IoT base stations or an additionaly layer of mobile LoRa base stations (Tier2).

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In recent years,  drones have been used to transport payloads to remote and difficult access areas. A payload delivery with assisted relay system of two unmanned aerial vehicles (UAVs) is implemented.  A local and web remote monitoring and control from a ground control station (GCS) for a pre-planned autonomous trajectory flight is developed in this work.
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This is the dataset for the paper Bayesian Inference of Sector Orientation in LTE Networks based on End-User Measurements published at VTC 2021 - Fall.

It includes a set of Drive-Test RSRP Pathloss Measurements with their relative position to the corresponding eNodeB. In total it contains data for 91 three-sector eNodeBs, which results in  273 sectors.

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The dataset consists of training and test data and label matrices for single-pixel compressive DoA estimation for mmWave metasurface. The dataset will be uploaded soon. Currently, a small part of the dataset can be accessed through this repository. For detailed information, please visit Graph Attention Network Based Single-Pixel Compressive Direction of Arrival Estimation through https://arxiv.org/abs/2109.05466

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The Internet of things (IoT) has emerged as a topic of intense interest among the research and industrial community as it has had a revolutionary impact on human life. The rapid growth of IoT technology has revolutionized human life by inaugurating the concept of smart devices, smart healthcare, smart industry, smart city, smart grid, among others. IoT devices’ security has become a serious concern nowadays, especially for the healthcare domain, where recent attacks exposed damaging IoT security vulnerabilities. Traditional network security solutions are well established.

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In this appendix, the tested implementation in Matlab of our 2D-TDOA localization algorithm is given for the easier repetition of the obtained results and the future hardware implementation, due to the complexity of the formulas (25)-(31).

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Wide area control (WAC) in smart grid requires low-latency communications across the grid to transfer various control commands and Phasor Measurement Unit (PMU) measurements. \textcolor{red}{Smart grid communications are generally implemented between multiple control centers, between transformer substations and control centers, and between power plants and control centers}.

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