Communications
This is the example dataset and source code of the paper "A Generalized Channel Dataset Generator for 5G New Radio Systems Based on Ray-Tracing" , and the data generator can be downloaded for free by researchers.
The datagenerator_raytrace3.0 is now support for mm-wave (28GHz+) channel state information.
The advantages of our dataset are as follows:
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To deal with the large-scale dataset requirements, this letter models the channel according to 5G NR stan- dard published by 3GPP, and provides a 5G NR channel datasets generator based on CDL channel model.
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We present detailed derivation of probability functions of differential ad-hoc detector and coherent detectors of XOR H-map for 2 (differentially encoded) BPSK source in H-MAC channel. Matlab script-files for (analytical) H-BER computation are provided.
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Any work using this dataset should cite the following paper:
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The measurement dataset consists of reflected received power from different shaped and sized metallic reflectors at 28 GHz in the indoor corridor and outdoor open area. PXI channel sounder from National Instruments was used for measurements. Horn antennas of gain 17 dBi were used at the transmitter and receiver. The measurements consisted of three flat square metallic reflectors of sizes 0.84 × 0.84 m^2 , 0.61 × 0.61 m^2 , and 0.3 × 0.3 m^2 , a sphere, and a cylinder. The effect of size and shape of the reflectors on the coverage was analyzed in the indoor corridor and outdoor open area.
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Please cite the following paper when using this dataset:
N. Thakur, "Twitter Big Data as a Resource for Exoskeleton Research: A Large-Scale Dataset of about 140,000 Tweets from 2017–2022 and 100 Research Questions", Journal of Analytics, Volume 1, Issue 2, 2022, pp. 72-97, DOI: https://doi.org/10.3390/analytics1020007
Abstract
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A synthetic signal dataset of 12 different modulations (including PSK, QPSK, 8PSK, QFSK, 8FSK, 16APSK, 16QAM, 64QAM, 4PAM, LFM, DSB-SC, and SSBSC) with different DOAs (discrete angles ranging from -60° to 60° with the step size of 1°) is generated using MATLAB 2021a. Regarding the signal model configuration for the data generation, we specify a uniform linear antenna array of M = 5 elements to acquire incoming signals having N = 1024 envelope complex samples, thus conducting an I/Q data array of size 1024 × 2 × 5.
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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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