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...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-02-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/19/4/841 |
| _version_ | 1811299844275306496 |
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| author | Di He Xin Chen Ling Pei Lingge Jiang Wenxian Yu |
| author_facet | Di He Xin Chen Ling Pei Lingge Jiang Wenxian Yu |
| author_sort | Di He |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-04-13T06:42:44Z |
| format | Article |
| id | doaj.art-3804a63963ed4d5d887c163a65ab9641 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-13T06:42:44Z |
| publishDate | 2019-02-01 |
| publisher | MDPI AG |
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| series | Sensors |
| spelling | doaj.art-3804a63963ed4d5d887c163a65ab96412022-12-22T02:57:41ZengMDPI 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 |
| 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 |
| title | 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_short | 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 |
| 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 |
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