Title :
A Novel Sequential Spectrum Sensing Method via Stochastic Resonance
Author :
Rui Gao ; Zan Li ; Peihan Qi ; Mengqiu Yang
Author_Institution :
State Key Lab. of Integrated Service Networks, Xidian Univ., Xi´an, China
Abstract :
As spectrum sensing detects the presence of primary user (PU) signal, an efficient and reliable spectrum sensing scheme plays a critical role in cognitive radio (CR). In this paper, a novel spectrum sensing method via stochastic resonance (SR) under low signal-to-noise ratio (SNR) is presented. It is shown that the introducing of suitable additional noise can enhance sequential energy detector (SED). Theoretical analysis and the optimal SR noise probability distribution function (PDF) are given. Simulation results show that in comparison with traditional sequential energy detection, our method delivers considerable reduction on the average sample number (ASN), while maintaining a comparable detection performance under low SNR.
Keywords :
cognitive radio; radio spectrum management; radiofrequency interference; resonance; signal detection; signal sampling; statistical distributions; stochastic processes; ASN; CR; PDF; PU signal; SED; SNR; SR noise probability distribution function; average sample number; cognitive radio; primary user signal; sequential energy detection; sequential energy detector; sequential spectrum sensing method; signal-to-noise ratio; spectrum sensing scheme; stochastic resonance; Cognitive radio; Computational complexity; Gaussian distribution; Sensors; Signal to noise ratio; Simulation;
Conference_Titel :
Vehicular Technology Conference (VTC Fall), 2014 IEEE 80th
Conference_Location :
Vancouver, BC
DOI :
10.1109/VTCFall.2014.6965832
