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The umkc/networkslicing5g dataset (2022-03-22)

University of Missouri Kansas City 5G Dataset, 6G Dataset, Network Slicing, Wireless Dataset, eMBB, URLLC, mMTC. DOI: https://doi.org/10.15783/k0w0-js18

Contributed by Anurag Thantharate, Cory Beard, Rahul Paropkari, Vijay Walunj.

We have created a Deep Learning model for 5G and Network Slicing. (eMBB, URLLC, IoT). I encourage developers and researchers working on the 4G/LTE, 5G, 6G and similar interest to use and provide feedback: Our research can be found at 1. IEEE paper "DeepSlice: A Deep Learning Approach towards an Efficient and Reliable Network Slicing in 5G Networks" (https://ieeexplore.ieee.org/document/8993066) 2. IEEE paper "Secure5G: A Deep Learning Framework Towards a Secure Network Slicing in 5G and Beyond" (https://ieeexplore.ieee.org/document/9031158)

 details of the umkc/networkslicing5g dataset (2022-03-22)

This dataset contains the following traceset:

  1. 5g
    5G Dataset

     quick access to download the traceset
 4 contributors US flag
 how to cite this dataset