Advanced optical modulation formats identification and signal-to-noise-ratio estimation based on VGG16

Xiaowei Dong; Zhihui Yu

doi:10.1117/12.2653310

15 December 2022 Advanced optical modulation formats identification and signal-to-noise-ratio estimation based on VGG16

Xiaowei Dong, Zhihui Yu

Author Affiliations +

Proceedings Volume 12478, Thirteenth International Conference on Information Optics and Photonics (CIOP 2022); 124781G (2022) https://doi.org/10.1117/12.2653310
Event: Thirteenth International Conference on Information Optics and Photonics (CIOP 2022), 2022, Xi'an, China

Abstract

In this paper, we adopt VGG-16 deep learning model and signal constellation diagrams to identify five different types of advanced optical modulation formats: BPSK, 4QAM, QPSK, 8QAM, 8PSK. 100% identification accuracy and no confusion are achieved for signal-to-noise ratio (SNR) higher than 8dB. Compared with the methods have been reported, the proposed method has the advantages of not requiring manual feature extraction, having the ability to identify the modulation format with high accuracy and to estimate the SNR.

Citation Download Citation

Xiaowei Dong and Zhihui Yu "Advanced optical modulation formats identification and signal-to-noise-ratio estimation based on VGG16", Proc. SPIE 12478, Thirteenth International Conference on Information Optics and Photonics (CIOP 2022), 124781G (15 December 2022); https://doi.org/10.1117/12.2653310

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE