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Dataset for paper Y. Ma, S. Mosleh and J. Coder, "Analyzing 5G NR-U and WiGig Coexistence with Multiple-Beam Directional LBT," 2022 IEEE 19th Annual Consumer Communications & Networking Conference (CCNC), 2022, pp. 272-275, doi: 10.1109/CCNC49033.2022.9700690

This project produces synthetic datasets of spectrum sharing simulation results (I/Q data, metadata, and KPIs).

About this Dataset

Updated: 2024-02-22
Metadata Last Updated: 2022-03-09 00:00:00
Date Created: N/A
Views:
Data Provided by:
wireless coexistence
Dataset Owner: N/A

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Table representation of structured data
Title Dataset for paper Y. Ma, S. Mosleh and J. Coder, "Analyzing 5G NR-U and WiGig Coexistence with Multiple-Beam Directional LBT," 2022 IEEE 19th Annual Consumer Communications & Networking Conference (CCNC), 2022, pp. 272-275, doi: 10.1109/CCNC49033.2022.9700690
Description This project produces synthetic datasets of spectrum sharing simulation results (I/Q data, metadata, and KPIs).
Modified 2022-03-09 00:00:00
Publisher Name National Institute of Standards and Technology
Contact mailto:yao.ma@nist.gov
Keywords wireless coexistence , spectrum sharing , machine learning , wireless communications and networks , 4G , 5G , 6G , Wi-Fi
{
    "identifier": "ark:\/88434\/mds2-2576",
    "accessLevel": "public",
    "references": [
        "https:\/\/www.nist.gov\/publications\/analyzing-5g-nr-u-and-wigig-coexistence-multiple-beam-directional-lbt"
    ],
    "contactPoint": {
        "hasEmail": "mailto:yao.ma@nist.gov",
        "fn": "Yao Ma"
    },
    "programCode": [
        "006:045"
    ],
    "@type": "dcat:Dataset",
    "landingPage": "https:\/\/data.nist.gov\/od\/id\/mds2-2576",
    "description": "This project  produces  synthetic  datasets of  spectrum sharing simulation results (I\/Q data, metadata, and KPIs).",
    "language": [
        "en"
    ],
    "title": "Dataset for  paper Y. Ma, S. Mosleh and J. Coder, \"Analyzing 5G NR-U and WiGig Coexistence with Multiple-Beam Directional LBT,\" 2022 IEEE 19th Annual Consumer Communications & Networking Conference (CCNC), 2022, pp. 272-275, doi: 10.1109\/CCNC49033.2022.9700690",
    "distribution": [
        {
            "downloadURL": "https:\/\/data.nist.gov\/od\/ds\/mds2-2576\/CCNC22.zip",
            "mediaType": "application\/x-zip-compressed"
        },
        {
            "downloadURL": "https:\/\/data.nist.gov\/od\/ds\/ark:\/88434\/mds2-2576\/2576_README.txt",
            "mediaType": "text\/plain"
        },
        {
            "downloadURL": "https:\/\/data.nist.gov\/od\/ds\/ark:\/88434\/mds2-2576\/2576_README.txt.sha256",
            "mediaType": "text\/plain"
        }
    ],
    "license": "https:\/\/www.nist.gov\/open\/license",
    "bureauCode": [
        "006:55"
    ],
    "modified": "2022-03-09 00:00:00",
    "publisher": {
        "@type": "org:Organization",
        "name": "National Institute of Standards and Technology"
    },
    "accrualPeriodicity": "irregular",
    "theme": [
        "Advanced Communications:Wireless (RF)"
    ],
    "keyword": [
        "wireless coexistence",
        "spectrum sharing",
        "machine learning",
        "wireless communications and networks",
        "4G",
        "5G",
        "6G",
        "Wi-Fi"
    ]
}

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