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Over 34,000 frames from 60 commercial-off-the-shelf ZigBee devices were collected in various scenarios including indoor/outdoor and line-of-sight/non-line-of-sight (LOS/NLOS). The ZigBee devices are hybrid, with 36 equipped with power amplifiers and the other 24 not. The ZigBee device uses the CC2530 chip, while the power amplifier is the RFX2401C chip. The signal frames in each scenario are placed in a separate folder, where all device numbers are fixed. Each frame reaches its maximum length, which includes 266 symbols.
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This dataset is associated with the manuscript entitled "Data-efficient Human Walking Speed Intent Inference". The data represent the measurements taken from 15 able-bodied human subjects as the made speed changes while walking on a treadmill. Each subject is associated with a .mat file that contains 8 variables. Four variables are associated with the training dataset while four are associated with the experimental testing protocol.
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Dataset: IQ samples of LTE, 5G NR, WiFi, ITS-G5, and C-V2X PC5
Thes dataset comprises IQ samples captured from ITSG-5, C-V2X PC5, WiFi, LTE, 5G NR and Noise. Six different dataset bunches are collected at sampling rates of 1, 5, 10, 15 , 20, and 25 Msps. In each dataset cluster, 7500 examples are collected from each considered technology. The dataset size at each considered sampling rate is 7500 X M, where M can be 44, 220, 440, 660, 880, and 1100 for a sampling rate of 1, 5, 10, 15 , 20, and 25 Msps,respectively.
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