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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.

About this Dataset

Updated: 2024-02-22
Metadata Last Updated: 2021-05-27 00:00:00
Date Created: N/A
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Data Provided by:
Sensing
Dataset Owner: N/A

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Table representation of structured data
Title Dataset of channels and received IEEE 802.11ay signals for sensing applications in the 60GHz band
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.
Modified 2021-05-27 00:00:00
Publisher Name National Institute of Standards and Technology
Contact mailto:steve.blandino@nist.gov
Keywords Sensing , communication , millimeter wave , dataset , machine learning , deep learning , channel model , IEEE 802.11ay , IEEE 802.11bf
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    "theme": [
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        "communication",
        "millimeter wave",
        "dataset",
        "machine learning",
        "deep learning",
        "channel model",
        "IEEE 802.11ay",
        "IEEE 802.11bf"
    ]
}

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