Signal Detection Algorithm Design Based on Stochastic Resonance Technology Under Low Signal-to-Noise Ratio

In the current 4th generation (4G) communication network, the base station with the same frequency transmission makes a serious interference among adjacent cells, and information transmission is susceptible to interference such as channel multipath fading and occlusion effect. Detecting effectively...

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Veröffentlicht in:Shanghai jiao tong da xue xue bao Jg. 24; H. 3; S. 328 - 334
Hauptverfasser: Jiang, Xiaolin, Diao, Ming, Qu, Susu
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Shanghai Shanghai Jiaotong University Press 01.06.2019
Springer Nature B.V
Schlagworte:
Algorithms
Architecture
Communications networks
Communications systems
Computer Science
Electrical Engineering
Energy
Engineering
Information processing
Interference
Life Sciences
Materials Science
Noise
Occlusion
Radio equipment
Resonance
Signal detection
Signal to noise ratio
Stochastic resonance
Technology
Wireless communications
Wireless networks
A
stochastic resonance
signal detection algorithm
4G communication network
TN 97
ISSN:1007-1172, 1674-8115, 1995-8188
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Zusammenfassung:In the current 4th generation (4G) communication network, the base station with the same frequency transmission makes a serious interference among adjacent cells, and information transmission is susceptible to interference such as channel multipath fading and occlusion effect. Detecting effectively spectrum signal under low signal-to-noise ratio (SNR), directly affects the whole performance of the wireless communication network system. This paper designs an energy signal detection algorithm based on stochastic resonance technology which transforms noise’s signal energy into useful signal energy, and improves output SNR. The energy signal detection algorithm realizes the function of providing effective detection of signal under low SNR, and promotes the performance of the whole communication system.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1007-1172
1674-8115
1995-8188
DOI:10.1007/s12204-019-2071-9