First Name: 
Merkebu
Last Name: 
Girmay

Datasets & Competitions

Dynamic Spectrum Sharing (DSS) is an enabler for a seamless transition from 4G Long TermEvolution (LTE) to 5G New Radio (NR) by utilizing existing LTE bands without static spectrum re-farming. In this paper, we propose a cross-band DSS scheme that utilizes the Multimedia BroadcastMulticast Service over a Single Frequency Network (MBSFN) feature of an LTE network and theMulticast Broadcast Service (MBS) feature of an NR network.

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262 Views

Dynamic Spectrum Sharing (DSS) is an enabler for a seamless transition from 4G Long TermEvolution (LTE) to 5G New Radio (NR) by utilizing existing LTE bands without static spectrum re-farming. In this paper, we propose a cross-band DSS scheme that utilizes the Multimedia BroadcastMulticast Service over a Single Frequency Network (MBSFN) feature of an LTE network and theMulticast Broadcast Service (MBS) feature of an NR network.

Categories:
175 Views

Dataset: IQ samples of LTE, 5G NR, WiFi, ITS-G5, and C-V2X PC5

Thes dataset comprises IQ samples captured from ITSG-5, C-V2X PC5, WiFi, LTE, 5G NR and Noise. Six different dataset bunches are collected at sampling rates of 1, 5, 10, 15 , 20, and 25 Msps. In each dataset cluster, 7500 examples are collected from each considered technology. The dataset size at each considered sampling rate is 7500 X M, where M can be 44, 220, 440, 660, 880, and 1100 for a sampling rate of 1, 5, 10, 15 , 20, and 25 Msps,respectively.

 

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1479 Views

Dataset for Identification of Saturated and Unsaturated WiFi Networks

The Dataset comprises the histogram of Inter-frame spacing for saturated and unsaturated WiFi networks.

In order to develop a CNN model that can classify saturated and unsaturated traffic in WiFi network, we prepared a large dataset that represents the traffic characteristics of both cases. 

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211 Views

Dataset for Identification of Saturated and Unsaturated WiFi Networks

The Dataset comprises the histogram of Inter-frame spacing for saturated and unsaturated WiFi networks.

In order to develop a CNN model that can classify saturated and unsaturated traffic in WiFi network, we prepared a large dataset that represents the traffic characteristics of both cases. 

Categories:
139 Views