# RSS data from smartwatch for Contact Tracing

 

This dataset was collected for the purpose to understand the proximity between any two smartwatches worn by human.

We used the Google's Wear OS based smartwatch, powered by a Qualcomm Snapdragon Wear 3100 processor, from Fossil sport to collect the data.

The smartwatch is powered by a Qualcomm Snapdragon Wear 3100 processor and has an internal memory of up to 1GB.

 

 

Two volunteers were required to wear the smartwatch on different hand and stand at a certain distance from each other.

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We have designed a ZYNQ SDR-based platform that utilizes real on-air 5G new radio (NR) signals to develop and test the performance of channel estimation for wireless channel estimators. On-air samples are obtained via the SDR platform to determine the unknown values of the channel response using known values at the pilot locations. We have collected extensive channel estimation data under a variety of scenarios: 1) line-of-sight (LOS), 2) LOS multipath and 3) non-LOS multipath. We have considered 2m,4m,6m test cases to simulate meter-level indoor positioning for indoor scenarios.

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This is the source code and dataset of the paper "Double QoS Guarantee for NOMA-Enabled

Massive MTC Networks".

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This data set, contains all the Duty Cycle (DC) measurements (Wi-Fi Channels 1 - 12 for 2.4GHz band), which exported through Energy Detection from Monitor DU3. The data set contains measurements between 2021-01-01 to 2021-12-20.

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This dataset consisting of MODBUS/TCP communication was created using the Factory.IO simulator (trial version is available). The dataset contains different scenarios that control different industrial processes. For each scenario, files are provided to capture normal communication and communication with anomalies. The purpose of the dataset is to support research and evaluation of anomaly detection methods in the field of ICS.

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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:

  • 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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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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