Cellular system identification using deep learning: GSM, UMTS and LTE

Khalid Alshathri; Hongtao Xia; Victor Lawrence; Yu Dong Yao

doi:10.1109/WOCC.2019.8770700

Cellular system identification using deep learning: GSM, UMTS and LTE

Khalid Alshathri
, Hongtao Xia
, Victor Lawrence
, Yu Dong Yao

Department of Electrical and Computer Engineering

Stevens Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Deep learning (DL) is an effective tool in artificial intelligence (AI), especially in image based and human behavior recognition applications. However, there are many applications that are not very well explored using the DL tools. The telecommunications and networking applications are among those applications that can be explored more extensively using DL. In this paper, the neural network is utilized to identify different cellular communications signals including GSM, UMTS, and LTE. Our study results show that the cellular system identification method achieves very good identification performance without any necessity to select signal features manually.

Original language	English
Title of host publication	2019 28th Wireless and Optical Communications Conference, WOCC 2019 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728106601
DOIs	https://doi.org/10.1109/WOCC.2019.8770700
State	Published - May 2019
Event	28th Wireless and Optical Communications Conference, WOCC 2019 - Beijing, China Duration: May 9 2019 → May 10 2019

Publication series

Name	2019 28th Wireless and Optical Communications Conference, WOCC 2019 - Proceedings

Conference

Conference	28th Wireless and Optical Communications Conference, WOCC 2019
Country/Territory	China
City	Beijing
Period	5/9/19 → 5/10/19

ASJC Scopus subject areas

Computer Networks and Communications
Information Systems and Management
Atomic and Molecular Physics, and Optics
Hardware and Architecture

Access to Document

10.1109/WOCC.2019.8770700

Cite this

Alshathri, K., Xia, H., Lawrence, V., & Yao, Y. D. (2019). Cellular system identification using deep learning: GSM, UMTS and LTE. In 2019 28th Wireless and Optical Communications Conference, WOCC 2019 - Proceedings Article 8770700 (2019 28th Wireless and Optical Communications Conference, WOCC 2019 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WOCC.2019.8770700

@inproceedings{e588fa120fe44490b2821342475119a6,

title = "Cellular system identification using deep learning: GSM, UMTS and LTE",

abstract = "Deep learning (DL) is an effective tool in artificial intelligence (AI), especially in image based and human behavior recognition applications. However, there are many applications that are not very well explored using the DL tools. The telecommunications and networking applications are among those applications that can be explored more extensively using DL. In this paper, the neural network is utilized to identify different cellular communications signals including GSM, UMTS, and LTE. Our study results show that the cellular system identification method achieves very good identification performance without any necessity to select signal features manually.",

author = "Khalid Alshathri and Hongtao Xia and Victor Lawrence and Yao, \{Yu Dong\}",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 28th Wireless and Optical Communications Conference, WOCC 2019 ; Conference date: 09-05-2019 Through 10-05-2019",

year = "2019",

month = may,

doi = "10.1109/WOCC.2019.8770700",

language = "English",

series = "2019 28th Wireless and Optical Communications Conference, WOCC 2019 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2019 28th Wireless and Optical Communications Conference, WOCC 2019 - Proceedings",

}

Alshathri, K, Xia, H, Lawrence, V & Yao, YD 2019, Cellular system identification using deep learning: GSM, UMTS and LTE. in 2019 28th Wireless and Optical Communications Conference, WOCC 2019 - Proceedings., 8770700, 2019 28th Wireless and Optical Communications Conference, WOCC 2019 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 28th Wireless and Optical Communications Conference, WOCC 2019, Beijing, China, 5/9/19. https://doi.org/10.1109/WOCC.2019.8770700

Cellular system identification using deep learning: GSM, UMTS and LTE. / Alshathri, Khalid; Xia, Hongtao; Lawrence, Victor et al.
2019 28th Wireless and Optical Communications Conference, WOCC 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. 8770700 (2019 28th Wireless and Optical Communications Conference, WOCC 2019 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Cellular system identification using deep learning

T2 - 28th Wireless and Optical Communications Conference, WOCC 2019

AU - Alshathri, Khalid

AU - Xia, Hongtao

AU - Lawrence, Victor

AU - Yao, Yu Dong

PY - 2019/5

Y1 - 2019/5

N2 - Deep learning (DL) is an effective tool in artificial intelligence (AI), especially in image based and human behavior recognition applications. However, there are many applications that are not very well explored using the DL tools. The telecommunications and networking applications are among those applications that can be explored more extensively using DL. In this paper, the neural network is utilized to identify different cellular communications signals including GSM, UMTS, and LTE. Our study results show that the cellular system identification method achieves very good identification performance without any necessity to select signal features manually.

AB - Deep learning (DL) is an effective tool in artificial intelligence (AI), especially in image based and human behavior recognition applications. However, there are many applications that are not very well explored using the DL tools. The telecommunications and networking applications are among those applications that can be explored more extensively using DL. In this paper, the neural network is utilized to identify different cellular communications signals including GSM, UMTS, and LTE. Our study results show that the cellular system identification method achieves very good identification performance without any necessity to select signal features manually.

UR - https://www.scopus.com/pages/publications/85070378928

UR - https://www.scopus.com/pages/publications/85070378928#tab=citedBy

U2 - 10.1109/WOCC.2019.8770700

DO - 10.1109/WOCC.2019.8770700

M3 - Conference contribution

T3 - 2019 28th Wireless and Optical Communications Conference, WOCC 2019 - Proceedings

BT - 2019 28th Wireless and Optical Communications Conference, WOCC 2019 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 9 May 2019 through 10 May 2019

ER -

Alshathri K, Xia H, Lawrence V, Yao YD. Cellular system identification using deep learning: GSM, UMTS and LTE. In 2019 28th Wireless and Optical Communications Conference, WOCC 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2019. 8770700. (2019 28th Wireless and Optical Communications Conference, WOCC 2019 - Proceedings). doi: 10.1109/WOCC.2019.8770700

Cellular system identification using deep learning: GSM, UMTS and LTE

Abstract

Publication series

Conference

ASJC Scopus subject areas

Access to Document

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