Datasets

Datasets of Indoor Wireless Channel Measurements for Machine Learning Applications

Adriano Pastore, Armin Ghani, Carles Antón-Haro

This is a simple dataset of raw IQ measurements on a point-to-point wireless indoor channel, captured in a static laboratory environment. A sequence of random symbols (either QPSK symbols or random Gaussian symbols) are passed through a raised-root-cosine filter and modulated to different frequencies (433 MHz, 708 MHz, 2450 MHz). These measurements are carried out for varying signal-to-noise conditions (approximately 0 dB, 10 dB, 20 dB, estimated pre-measurement). These datasets may be used, for example, for data-driven channel modeling with state-of-the-art AI and machine learning algorithms (e.g., generative adversarial networks), for validating conventional channel models against real measurements, or for investigating the properties of real wireless channels.

Datasets of Indoor UWB Measurements for Ranging and Positioning in Good and Challenging Scenarios

Ana Moragrega

This is a dataset of ranging and positioning measurements collected from an UWB development board.
The Real Time Location System based on UWB is set up in a laboratory. Data were captured in the static laboratory environment with different conditions that affects to the positioning performance. In the lab, scenarios with different propagation conditions between the nodes and different geometries were set up. We consider good, challenging, and intermediate scenarios with: Line of Sight (LOS) and Non-LOS propagation conditions as well as good and challenging geometries. These datasets may be used, for example, for investing and validating ranging and positioning algorithms in different scenarios.