Dataset of channels and received IEEE 802.11ay signals for sensing applications in the 60GHz band
The dataset can be used to develop and test algorithms for communication and sensing in the 60GHz band. The dataset consists of synthetically generated indoor mm-wave channels between a MIMO transmitter and a MIMO receivers. Multiple targets are moving in the room. Number of targets, velocity of each target and trajectory are randomized across the dataset. The dataset contains also noisy received IEEE 802.11ay channel estimation fields. The dataset is suitable for development and testing of machine/deep learning algorithms. The dataset can be used to participate to the ITU AI/ML 5G Challenge. For information on the challenge and registration, please refer to: https://challenge.aiforgood.itu.int/match/matchitem/38. The challenge dataset relies on the open-source software available at: https://github.com/usnistgov/PS-002-WALDO.
Complete Metadata
| @type | dcat:Dataset |
|---|---|
| accessLevel | public |
| accrualPeriodicity | irregular |
| bureauCode |
[
"006:55"
]
|
| contactPoint |
{
"fn": "Steve Blandino",
"hasEmail": "mailto:steve.blandino@nist.gov"
}
|
| description | The dataset can be used to develop and test algorithms for communication and sensing in the 60GHz band. The dataset consists of synthetically generated indoor mm-wave channels between a MIMO transmitter and a MIMO receivers. Multiple targets are moving in the room. Number of targets, velocity of each target and trajectory are randomized across the dataset. The dataset contains also noisy received IEEE 802.11ay channel estimation fields. The dataset is suitable for development and testing of machine/deep learning algorithms. The dataset can be used to participate to the ITU AI/ML 5G Challenge. For information on the challenge and registration, please refer to: https://challenge.aiforgood.itu.int/match/matchitem/38. The challenge dataset relies on the open-source software available at: https://github.com/usnistgov/PS-002-WALDO. |
| distribution |
[
{
"title": "DOI Access for Dataset of channels and received IEEE 802.11ay signals for sensing applications in the 60GHz band",
"accessURL": "https://doi.org/10.18434/mds2-2417"
},
{
"title": "GitHub Access to Download",
"format": "text/html",
"accessURL": "https://github.com/usnistgov/PS-002-WALDO",
"description": "GitHub Access to Download"
},
{
"title": "Data file listing",
"mediaType": "application/vnd.ms-excel",
"description": "CSV file containing the download URL for the file in the dataset",
"downloadURL": "https://data.nist.gov/od/ds/mds2-2417/mds2-2417-filelisting.csv"
},
{
"title": "Instructions to download the dataset",
"mediaType": "text/plain",
"description": "Instructions to download the dataset",
"downloadURL": "https://data.nist.gov/od/ds/mds2-2417/Instructions%20to%20download%20the%20dataset.txt"
},
{
"title": "SHA256 File for Instructions to download the dataset",
"mediaType": "text/plain",
"downloadURL": "https://data.nist.gov/od/ds/mds2-2417/Instructions%20to%20download%20the%20dataset.txt.sha256"
},
{
"title": "SHA256 File for Data file listing",
"mediaType": "text/plain",
"downloadURL": "https://data.nist.gov/od/ds/mds2-2417/mds2-2417-filelisting.csv.sha256"
}
]
|
| identifier | ark:/88434/mds2-2417 |
| issued | 2021-07-19 |
| keyword |
[
"IEEE 802.11ay",
"IEEE 802.11bf",
"Sensing",
"channel model",
"communication",
"dataset",
"deep learning",
"machine learning",
"millimeter wave"
]
|
| landingPage | https://data.nist.gov/od/id/mds2-2417 |
| language |
[
"en"
]
|
| license | https://www.nist.gov/open/license |
| modified | 2021-05-27 00:00:00 |
| programCode |
[
"006:045"
]
|
| publisher |
{
"name": "National Institute of Standards and Technology",
"@type": "org:Organization"
}
|
| theme |
[
"Advanced Communications:Wireless (RF)",
"Information Technology:Mobile"
]
|
| title | Dataset of channels and received IEEE 802.11ay signals for sensing applications in the 60GHz band |
