dichasus-cf1x-part1 Dataset: Distributed Antenna Setup in Industrial Environment, Day 2, First Part

Distributed antenna setup with line-of-sight (LoS) and non-line-of-sight (NLoS) channels, measured in the Arena2036 research factory campus environment.

Four antenna arrays with 8 antennas each distributed at the corners of an L-shaped area with a scatterer in between. Due to a technical problem, 8 antennas (part of arrays B, C and D) are missing from the dataset.

50.000 MHz

Signal Bandwidth

1024

OFDM Subcarriers

27510

Data Points

2185.8 s

Total Duration

5.4 GB

Total Download Size

24

Number of Antennas

Indoor

Type of Environment

1.272000 GHz

Carrier Frequency

Distributed

Antenna Setup

3D Tachymeter

Position-Tagged

Experiment Setup

Data Analysis

Antenna Configuration

Antenna 1: Antenna Array A

This array has a vertical spacing of 0.118m and a horizontal spacing of 0.118m. In the dataset's cartesian coordinate system, its center is located at [2.6747 -13.8973 1.560075] and the antenna points in direction [-0.4499506 0.89246853 0.03231686].
Antenna Channel Assignments
4 1 11 13
20 3 5 9

Antenna 2: Antenna Array B

This array has a vertical spacing of 0.118m and a horizontal spacing of 0.118m. In the dataset's cartesian coordinate system, its center is located at [-11.250275 -9.689025 1.5336] and the antenna points in direction [0.79575318 0.60534027 0.01843999].
Antenna Channel Assignments
16 10
22 15 18

Antenna 3: Antenna Array C

This array has a vertical spacing of 0.118m and a horizontal spacing of 0.118m. In the dataset's cartesian coordinate system, its center is located at [-1.531375 -15.0595 1.5772] and the antenna points in direction [0.21108544 0.97732106 0.0169259].
Antenna Channel Assignments
2 0 7
8 23 21

Antenna 4: Antenna Array D

This array has a vertical spacing of 0.118m and a horizontal spacing of 0.118m. In the dataset's cartesian coordinate system, its center is located at [-12.684425 -4.483325 1.78985] and the antenna points in direction [0.99369031 -0.08476847 0.073443].
Antenna Channel Assignments
6 19
14 17 12

Python: Import with TensorFlow

#!/usr/bin/env python3
import tensorflow as tf

raw_dataset = tf.data.TFRecordDataset(["tfrecords/dichasus-cf12.tfrecords"])

feature_description = {
	"cfo": tf.io.FixedLenFeature([], tf.string, default_value = ''),
	"csi": tf.io.FixedLenFeature([], tf.string, default_value = ''),
	"gt-interp-age-tachy": tf.io.FixedLenFeature([], tf.float32, default_value = 0),
	"pos-tachy": tf.io.FixedLenFeature([], tf.string, default_value = ''),
	"snr": tf.io.FixedLenFeature([], tf.string, default_value = ''),
	"time": tf.io.FixedLenFeature([], tf.float32, default_value = 0),
}
			
def record_parse_function(proto):
	record = tf.io.parse_single_example(proto, feature_description)

	# Measured carrier frequency offset between MOBTX and each receive antenna.
	cfo = tf.ensure_shape(tf.io.parse_tensor(record["cfo"], out_type = tf.float32), (24))

	# Channel coefficients for all antennas, over all subcarriers, real and imaginary parts
	csi = tf.ensure_shape(tf.io.parse_tensor(record["csi"], out_type = tf.float32), (24, 1024, 2))

	# Time in seconds to closest known tachymeter position. Indicates quality of linear interpolation.
	gt_interp_age_tachy = tf.ensure_shape(record["gt-interp-age-tachy"], ())

	# Position of transmitter determined by a tachymeter pointed at a prism mounted on top of the antenna, in meters (X / Y / Z coordinates)
	pos_tachy = tf.ensure_shape(tf.io.parse_tensor(record["pos-tachy"], out_type = tf.float64), (3))

	# Signal-to-Noise ratio estimates for all antennas
	snr = tf.ensure_shape(tf.io.parse_tensor(record["snr"], out_type = tf.float32), (24))

	# Timestamp since start of measurement campaign, in seconds
	time = tf.ensure_shape(record["time"], ())

	return cfo, csi, gt_interp_age_tachy, pos_tachy, snr, time
			
dataset = raw_dataset.map(record_parse_function, num_parallel_calls = tf.data.experimental.AUTOTUNE)

# Optional: Cache dataset in RAM for faster training
dataset = dataset.cache()

Reference Channel Compensation

For this dataset, we are able to provide estimated antenna-specific carrier phase and sampling time offsets. These offsets occur due to the fact that the reference transmitter channel is not perfectly frequency-flat. To learn more about why these offsets occur and about their compensation, visit our offset calibration tutorial on this topic. Note that the estimates provided here are "best-effort" calculations. The phase and time offsets between antennas in the same array are usually very accurate, but for antennas that are spaced far apart, the results may be less precise. The offset are constant over the complete dataset.

How to Cite

Please refer to the home page for information on how to cite any of our datasets in your research. For this dataset in particular, you may use the following BibTeX:

@data{dataset-dichasus-cf1x-part1,
	author    = {Florian Euchner and Marc Gauger},
	publisher = {DaRUS},
	title     = {{CSI Dataset dichasus-cf1x-part1: Distributed Antenna Setup in Industrial Environment, Day 2, First Part}},
	doi       = {doi:10.18419/darus-3150},
	url       = {https://doi.org/doi:10.18419/darus-3150},
	year      = {2022}
}

Download

This dataset consists of 1 file. Descriptions of this file as well as download links are provided below.

dichasus-cf12
Textual Description

The robot takes a similar circular trajectory multiple times, sometimes alternating between two paths.

5.4 GB

File Size

27510

Points

2185.8 s

Duration