Paper Info
Title
Joint Rapid Spectrum Scanning and Signal Feature Recognition Scheme Using Compressed Sensing and Cyclostationary Technologies.
Abstract
This paper proposes a joint rapid spectrum scanning and signal feature recognition scheme by using both compressed sensing (CS) and cyclostationary technologies to solve the paradox of rapid spectrum scanning and accurate signal feature recognition. First, a new system architecture for signal feature recognition is designed based on rapid spectrum scanning results to decrease the times of proposed signal feature recognition scheme. Moreover, an improved CS technology is brought forward to accelerate the sensing speed without reconstructing received signals for a rapid spectrum scanning. And a tunable compression gain is proposed to reduce both computation complexity and sampling rate based on the difference of modulation mode and symbol rate for various signals. To further reduce the effect of noise on the modulation classification performance, a novel noise reduction scheme is proposed using the cyclostationary technology. Results prove that proposed scheme can achieve both rapid spectrum scanning and accurate signal feature recognition simultaneously. Furthermore, it can reduce the sampling rate for CS over 30% and achieves a signal detection gain of 2–3 dB with signal to noise ratio constraints.
Year
DOI
Venue
2017
10.1007/s11277-017-4706-1
Wireless Personal Communications
Keywords
Field
DocType
Compressed sensing,Cyclostationary,Modulation classification
Noise reduction,Detection theory,Computer science,Symbol rate,Sampling (signal processing),Feature recognition,Signal-to-noise ratio,Real-time computing,Electronic engineering,Speech recognition,Compressed sensing,Cyclostationary process
Journal
Volume
Issue
ISSN
97
3
0929-6212
Citations 
PageRank 
References 
0
0.34
16
Authors
5
Name
Order
Citations
PageRank
Yifan Zhang13010.85
Qixun Zhang215728.59
Xuan Fu311.40
Yucheng Tian400.34
Zhiyong Feng514829.14