TY - GEN
T1 - 5G Signal Identification Using Deep Learning
AU - Alhazmi, Mohsen H.
AU - Alymani, Mofadal
AU - Alhazmi, Hatim
AU - Almarhabi, Alhussain
AU - Samarkandi, Abdullah
AU - Yao, Yu Dong
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/5
Y1 - 2020/5
N2 - Spectrum awareness, including identifying different types of signals, is very important in a cellular system environment. In this paper, a neural network is utilized to identify 5G signals among different cellular communications signals, including Long-Term Evolution (LTE) and Universal Mobile Telecommunication Service (UMTS). We explore the use of deep learning in wireless communications systems. We consider the effects of training dataset size, features extracted, and channel fading in our study. Experiment results demonstrate the effectiveness of deep learning neural networks in identifying cellular system signals, including UMTS, LTE, and 5G.
AB - Spectrum awareness, including identifying different types of signals, is very important in a cellular system environment. In this paper, a neural network is utilized to identify 5G signals among different cellular communications signals, including Long-Term Evolution (LTE) and Universal Mobile Telecommunication Service (UMTS). We explore the use of deep learning in wireless communications systems. We consider the effects of training dataset size, features extracted, and channel fading in our study. Experiment results demonstrate the effectiveness of deep learning neural networks in identifying cellular system signals, including UMTS, LTE, and 5G.
KW - Classification
KW - Convolutional Neural Network (CNN)
KW - Deep Learning (DL)
KW - Fifth Generation New Radio (5G)
KW - Long-Term Evolution (LTE)
KW - Machine learning (ML)
KW - Rayleigh Fading
KW - Universal Mobile Telecommunication Service (UMTS)
UR - http://www.scopus.com/inward/record.url?scp=85091897710&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85091897710&partnerID=8YFLogxK
U2 - 10.1109/WOCC48579.2020.9114912
DO - 10.1109/WOCC48579.2020.9114912
M3 - Conference contribution
AN - SCOPUS:85091897710
T3 - 2020 29th Wireless and Optical Communications Conference, WOCC 2020
BT - 2020 29th Wireless and Optical Communications Conference, WOCC 2020
T2 - 29th Wireless and Optical Communications Conference, WOCC 2020
Y2 - 1 May 2020 through 2 May 2020
ER -