Improvement of Noise Uncertainty and Signal-To-Noise Ratio Wall in Spectrum Sensing Based on Optimal Stochastic Resonance

Noise uncertainty and signal-to-noise ratio (SNR) wall are two very serious problems in spectrum sensing of cognitive radio (CR) networks, which restrict the applications of some conventional spectrum sensing methods especially under low SNR circumstances. In this study, an optimal dynamic stochasti...

Full description

Bibliographic Details
Main Authors: Di He, Xin Chen, Ling Pei, Lingge Jiang, Wenxian Yu
Format: Article
Language:English
Published: MDPI AG 2019-02-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/19/4/841
id doaj-3804a63963ed4d5d887c163a65ab9641
record_format Article
spelling doaj-3804a63963ed4d5d887c163a65ab96412020-11-25T01:11:21ZengMDPI AGSensors1424-82202019-02-0119484110.3390/s19040841s19040841Improvement of Noise Uncertainty and Signal-To-Noise Ratio Wall in Spectrum Sensing Based on Optimal Stochastic ResonanceDi He0Xin Chen1Ling Pei2Lingge Jiang3Wenxian Yu4Shanghai Key Laboratory of Navigation and Location-Based Services, Shanghai Jiao Tong University, Shanghai 200240, ChinaShanghai Key Laboratory of Navigation and Location-Based Services, Shanghai Jiao Tong University, Shanghai 200240, ChinaShanghai Key Laboratory of Navigation and Location-Based Services, Shanghai Jiao Tong University, Shanghai 200240, ChinaDepartment of Electronic Engineering, Shanghai Jiao Tong University, Shanghai 200240, ChinaShanghai Key Laboratory of Intelligent Sensing and Recognition, Shanghai Jiao Tong University, Shanghai 200240, ChinaNoise uncertainty and signal-to-noise ratio (SNR) wall are two very serious problems in spectrum sensing of cognitive radio (CR) networks, which restrict the applications of some conventional spectrum sensing methods especially under low SNR circumstances. In this study, an optimal dynamic stochastic resonance (SR) processing method is introduced to improve the SNR of the receiving signal under certain conditions. By using the proposed method, the SNR wall can be enhanced and the sampling complexity can be reduced, accordingly the noise uncertainty of the received signal can also be decreased. Based on the well-studied overdamped bistable SR system, the theoretical analyses and the computer simulations verify the effectiveness of the proposed approach. It can extend the application scenes of the conventional energy detection especially under some serious wireless conditions especially low SNR circumstances such as deep wireless signal fading, signal shadowing and multipath fading.https://www.mdpi.com/1424-8220/19/4/841cognitive radio (CR)spectrum sensingenergy detector (ED)signal-to-noise ratio (SNR) walloptimal stochastic resonance
collection DOAJ
language English
format Article
sources DOAJ
author Di He
Xin Chen
Ling Pei
Lingge Jiang
Wenxian Yu
spellingShingle Di He
Xin Chen
Ling Pei
Lingge Jiang
Wenxian Yu
Improvement of Noise Uncertainty and Signal-To-Noise Ratio Wall in Spectrum Sensing Based on Optimal Stochastic Resonance
Sensors
cognitive radio (CR)
spectrum sensing
energy detector (ED)
signal-to-noise ratio (SNR) wall
optimal stochastic resonance
author_facet Di He
Xin Chen
Ling Pei
Lingge Jiang
Wenxian Yu
author_sort Di He
title Improvement of Noise Uncertainty and Signal-To-Noise Ratio Wall in Spectrum Sensing Based on Optimal Stochastic Resonance
title_short Improvement of Noise Uncertainty and Signal-To-Noise Ratio Wall in Spectrum Sensing Based on Optimal Stochastic Resonance
title_full Improvement of Noise Uncertainty and Signal-To-Noise Ratio Wall in Spectrum Sensing Based on Optimal Stochastic Resonance
title_fullStr Improvement of Noise Uncertainty and Signal-To-Noise Ratio Wall in Spectrum Sensing Based on Optimal Stochastic Resonance
title_full_unstemmed Improvement of Noise Uncertainty and Signal-To-Noise Ratio Wall in Spectrum Sensing Based on Optimal Stochastic Resonance
title_sort improvement of noise uncertainty and signal-to-noise ratio wall in spectrum sensing based on optimal stochastic resonance
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2019-02-01
description Noise uncertainty and signal-to-noise ratio (SNR) wall are two very serious problems in spectrum sensing of cognitive radio (CR) networks, which restrict the applications of some conventional spectrum sensing methods especially under low SNR circumstances. In this study, an optimal dynamic stochastic resonance (SR) processing method is introduced to improve the SNR of the receiving signal under certain conditions. By using the proposed method, the SNR wall can be enhanced and the sampling complexity can be reduced, accordingly the noise uncertainty of the received signal can also be decreased. Based on the well-studied overdamped bistable SR system, the theoretical analyses and the computer simulations verify the effectiveness of the proposed approach. It can extend the application scenes of the conventional energy detection especially under some serious wireless conditions especially low SNR circumstances such as deep wireless signal fading, signal shadowing and multipath fading.
topic cognitive radio (CR)
spectrum sensing
energy detector (ED)
signal-to-noise ratio (SNR) wall
optimal stochastic resonance
url https://www.mdpi.com/1424-8220/19/4/841
work_keys_str_mv AT dihe improvementofnoiseuncertaintyandsignaltonoiseratiowallinspectrumsensingbasedonoptimalstochasticresonance
AT xinchen improvementofnoiseuncertaintyandsignaltonoiseratiowallinspectrumsensingbasedonoptimalstochasticresonance
AT lingpei improvementofnoiseuncertaintyandsignaltonoiseratiowallinspectrumsensingbasedonoptimalstochasticresonance
AT linggejiang improvementofnoiseuncertaintyandsignaltonoiseratiowallinspectrumsensingbasedonoptimalstochasticresonance
AT wenxianyu improvementofnoiseuncertaintyandsignaltonoiseratiowallinspectrumsensingbasedonoptimalstochasticresonance
_version_ 1725171518930944000