Deep Learning-Based Signal-To-Noise Ratio Estimation Using Constellation Diagrams

Joint Authors

Yang, Xi
Xie, Xiaojuan
Peng, Shengliang

Source

Mobile Information Systems

Issue

Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-9, 9 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2020-11-06

Country of Publication

Egypt

No. of Pages

9

Main Subjects

Telecommunications Engineering

Abstract EN

Signal-to-noise ratio (SNR) estimation is a fundamental task of spectrum management and data transmission.

Existing methods for SNR estimation usually suffer from significant estimation errors when SNR is low.

This paper proposes a deep learning (DL) based SNR estimation algorithm using constellation diagrams.

Since the constellation diagrams exhibit different patterns at different SNRs, the proposed algorithm achieves SNR estimation via constellation diagram recognition, which can be easily handled based on DL.

Three DL networks, AlexNet, InceptionV1, and VGG16, are utilized for DL based SNR estimation.

Experimental results show that the proposed algorithm always performs well, especially in low SNR scenarios.

American Psychological Association (APA)

Xie, Xiaojuan& Peng, Shengliang& Yang, Xi. 2020. Deep Learning-Based Signal-To-Noise Ratio Estimation Using Constellation Diagrams. Mobile Information Systems،Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1192522

Modern Language Association (MLA)

Yang, Xi…[et al.]. Deep Learning-Based Signal-To-Noise Ratio Estimation Using Constellation Diagrams. Mobile Information Systems No. 2020 (2020), pp.1-9.
https://search.emarefa.net/detail/BIM-1192522

American Medical Association (AMA)

Xie, Xiaojuan& Peng, Shengliang& Yang, Xi. Deep Learning-Based Signal-To-Noise Ratio Estimation Using Constellation Diagrams. Mobile Information Systems. 2020. Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1192522

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1192522