Communications
The dataset includes channel frequency response (CFR) data collected through an IEEE 802.11ax device for human activity recognition. This is the first dataset for Wi-Fi sensing with the IEEE 802.11ax standard which is the most updated Wi-Fi version available in commercial devices. The dataset has been collected within a single environment considering a single person as the purpose of the study was to evaluate the impact of communication parameters on the performance of sensing algorithms.
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Reconfigurable intelligent surfaces (RIS) are a core component considered in sixth generation (6G) communications. By utilizing an RIS prototype system in the 5 GHz band, this paper provides a comprehensive dataset of S21 channel measurements of various geometric arrangements of antennas and RIS. The dataset is provided in full on IEEE DataPort. Additionally, the in-detail documentation of the measurement setup, location, devices, geometries, and algorithms is available on GitHub.
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The dataset Provides S-parameter measurements of two ISO/ICE 14443-1 Coils with series capacitance compensation at 13.56 MHz under different spatial configurations of vertical and horizontal misalignment, inter-coil distance, and azimuthal tilt as indicated in the image. The dataset can be used for training of neural networks controlling adaptive impedance matching networks.
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Cars, mobile phones, and smart home devices already provide automatic speech recognition (ASR) by default. However, human machine interfaces (HMI) in industrial settings, as opposed to consumer settings, operate under different conditions and thus, present different design challenges. Voice control, arguably the most natural form of communication, has the potential to shorten complex command sequences and menu structures in order to directly execute a final command.
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The data is a truth table of a 22-variable 4-resilient Boolean function with nonlinearity 2095616.
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We propose an algorithm based on linear prediction that can perform both the lossless and near-lossless compression of RF signals. The proposed algorithm is coupled with two signal detection methods to determine the presence of relevant signals and apply varying levels of loss as needed. The first method uses spectrum sensing techniques, while the second one takes advantage of the error computed in each iteration of the Levinson-Durbin algorithm. These algorithms have been integrated as a new pre-processing stage into FAPEC, a data compressor first designed for space missions.
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This supplementary material includes the derivation of static coupling and radiative coupling between coils working at near-field/far-field hybrid regions.
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Update (07/30/2023): The dataset has been updated to be more realistic with specific characteristics described in [*].
We collect encrypted traffic from six widely-used Instant Messaging Applications (IMAs) installed on an Android device for descriptive and statistical analysis, as presented in our papers [*][**]. In particular, we collect traffic from:
1. Microsoft Teams,
2. Discord,
3. Facebook Messenger,
4. Signal,
5. Telegram, and
6. WhatsApp.
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Fifth-generation (5G) wireless systems increased the bandwidth, improved the speed, and shortened the latency of communications systems. Various channel models are developed to study 5G. These channel models reproduce the stochastic properties of multiple-input multiple-output (MIMO) antennas by generating wireless multipath components (MPCs). The MPCs that have similar properties in delay, angles of departure, and angles of arrival form clusters. The multipaths and multipath clusters serve as datasets and are clustered to understand the properties of 5G.
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