Discrete likelihood ratio test for intelligent signal recognition in software defined radio

Jefferson L. Xu; Meng Chu Zhou; Wei Su

doi:10.1109/WOCC.2010.5510597

Discrete likelihood ratio test for intelligent signal recognition in software defined radio

Jefferson L. Xu, Meng Chu Zhou, Wei Su

Electrical and Computer Engineering

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

4 Scopus citations

Abstract

Only very few computational complexity reduced automatic modulation recognition methods have been invented to satisfy the seamless demodulation requirement arising from software defined radio (SDR). Among them, a discrete likelihood ratio test (DLRT) based rapid estimation approach was introduced recently in our prior work and capable of identifying most of M-ary linear digital modulation schemes blindly in real-time. This paper intends to present its comprehensive performance evaluation results with a variety of classification cases.

Original language	English (US)
Title of host publication	WOCC2010 Technical Program - The 19th Annual Wireless and Optical Communications Conference
Subtitle of host publication	Converging Communications Around the Pacific
DOIs	https://doi.org/10.1109/WOCC.2010.5510597
State	Published - 2010
Event	19th Annual Wireless and Optical Communications Conference, WOCC2010: Converging Communications Around the Pacific - Shanghai, China Duration: May 14 2010 → May 15 2010

Publication series

Name	WOCC2010 Technical Program - The 19th Annual Wireless and Optical Communications Conference: Converging Communications Around the Pacific

Other

Other	19th Annual Wireless and Optical Communications Conference, WOCC2010: Converging Communications Around the Pacific
Country/Territory	China
City	Shanghai
Period	5/14/10 → 5/15/10

All Science Journal Classification (ASJC) codes

Computer Networks and Communications
Electrical and Electronic Engineering
Communication

Keywords

Adaptive modulation
Maximum likelihood ratio test
Modulation classification
Modulation recognition
Software defined radio

Access to Document

10.1109/WOCC.2010.5510597

Cite this

Xu, J. L., Zhou, M. C., & Su, W. (2010). Discrete likelihood ratio test for intelligent signal recognition in software defined radio. In WOCC2010 Technical Program - The 19th Annual Wireless and Optical Communications Conference: Converging Communications Around the Pacific Article 5510597 (WOCC2010 Technical Program - The 19th Annual Wireless and Optical Communications Conference: Converging Communications Around the Pacific). https://doi.org/10.1109/WOCC.2010.5510597

Xu, Jefferson L. ; Zhou, Meng Chu ; Su, Wei. / Discrete likelihood ratio test for intelligent signal recognition in software defined radio. WOCC2010 Technical Program - The 19th Annual Wireless and Optical Communications Conference: Converging Communications Around the Pacific. 2010. (WOCC2010 Technical Program - The 19th Annual Wireless and Optical Communications Conference: Converging Communications Around the Pacific).

@inproceedings{a1b720e38ad642b1a2969c97af59557f,

title = "Discrete likelihood ratio test for intelligent signal recognition in software defined radio",

abstract = "Only very few computational complexity reduced automatic modulation recognition methods have been invented to satisfy the seamless demodulation requirement arising from software defined radio (SDR). Among them, a discrete likelihood ratio test (DLRT) based rapid estimation approach was introduced recently in our prior work and capable of identifying most of M-ary linear digital modulation schemes blindly in real-time. This paper intends to present its comprehensive performance evaluation results with a variety of classification cases.",

keywords = "Adaptive modulation, Maximum likelihood ratio test, Modulation classification, Modulation recognition, Software defined radio",

author = "Xu, {Jefferson L.} and Zhou, {Meng Chu} and Wei Su",

year = "2010",

doi = "10.1109/WOCC.2010.5510597",

language = "English (US)",

isbn = "9781424475964",

series = "WOCC2010 Technical Program - The 19th Annual Wireless and Optical Communications Conference: Converging Communications Around the Pacific",

booktitle = "WOCC2010 Technical Program - The 19th Annual Wireless and Optical Communications Conference",

note = "19th Annual Wireless and Optical Communications Conference, WOCC2010: Converging Communications Around the Pacific ; Conference date: 14-05-2010 Through 15-05-2010",

}

Xu, JL, Zhou, MC & Su, W 2010, Discrete likelihood ratio test for intelligent signal recognition in software defined radio. in WOCC2010 Technical Program - The 19th Annual Wireless and Optical Communications Conference: Converging Communications Around the Pacific., 5510597, WOCC2010 Technical Program - The 19th Annual Wireless and Optical Communications Conference: Converging Communications Around the Pacific, 19th Annual Wireless and Optical Communications Conference, WOCC2010: Converging Communications Around the Pacific, Shanghai, China, 5/14/10. https://doi.org/10.1109/WOCC.2010.5510597

Discrete likelihood ratio test for intelligent signal recognition in software defined radio. / Xu, Jefferson L.; Zhou, Meng Chu; Su, Wei.
WOCC2010 Technical Program - The 19th Annual Wireless and Optical Communications Conference: Converging Communications Around the Pacific. 2010. 5510597 (WOCC2010 Technical Program - The 19th Annual Wireless and Optical Communications Conference: Converging Communications Around the Pacific).

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

TY - GEN

T1 - Discrete likelihood ratio test for intelligent signal recognition in software defined radio

AU - Xu, Jefferson L.

AU - Zhou, Meng Chu

AU - Su, Wei

PY - 2010

Y1 - 2010

N2 - Only very few computational complexity reduced automatic modulation recognition methods have been invented to satisfy the seamless demodulation requirement arising from software defined radio (SDR). Among them, a discrete likelihood ratio test (DLRT) based rapid estimation approach was introduced recently in our prior work and capable of identifying most of M-ary linear digital modulation schemes blindly in real-time. This paper intends to present its comprehensive performance evaluation results with a variety of classification cases.

AB - Only very few computational complexity reduced automatic modulation recognition methods have been invented to satisfy the seamless demodulation requirement arising from software defined radio (SDR). Among them, a discrete likelihood ratio test (DLRT) based rapid estimation approach was introduced recently in our prior work and capable of identifying most of M-ary linear digital modulation schemes blindly in real-time. This paper intends to present its comprehensive performance evaluation results with a variety of classification cases.

KW - Adaptive modulation

KW - Maximum likelihood ratio test

KW - Modulation classification

KW - Modulation recognition

KW - Software defined radio

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M3 - Conference contribution

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T3 - WOCC2010 Technical Program - The 19th Annual Wireless and Optical Communications Conference: Converging Communications Around the Pacific

BT - WOCC2010 Technical Program - The 19th Annual Wireless and Optical Communications Conference

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Y2 - 14 May 2010 through 15 May 2010

ER -

Xu JL, Zhou MC, Su W. Discrete likelihood ratio test for intelligent signal recognition in software defined radio. In WOCC2010 Technical Program - The 19th Annual Wireless and Optical Communications Conference: Converging Communications Around the Pacific. 2010. 5510597. (WOCC2010 Technical Program - The 19th Annual Wireless and Optical Communications Conference: Converging Communications Around the Pacific). doi: 10.1109/WOCC.2010.5510597

Discrete likelihood ratio test for intelligent signal recognition in software defined radio

Abstract

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All Science Journal Classification (ASJC) codes

Keywords

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