Abstract
Cognitive radio is considered an effective solution to spectrum shortages, which has been a significant issue in the next generation of wireless communications. In this paper, we focus on spectrum sensing under a low signal-to-noise-ratio (SNR) and noise fluctuation and propose a symmetric peaks-based spectrum sensing algorithm for modulated signals. First, we analyze the characteristics of the cyclic autocorrelation function of modulated signals, and construct a detection domain for detecting primary users based on the characteristics of the cyclic autocorrelation function of primary signals. Then, we introduce the significance level factor into the spectrum sensing, and develop a symmetric peaks criterion. Following this criterion, we propose a symmetric peaks-based spectrum sensing algorithm. Finally, we give the probabilities of detection and false alarm of the spectrum sensing algorithm, discuss the effect of the significance level factor on the spectrum sensing performance, and compare the complexity of the algorithm with that of other algorithms. The spectrum sensing algorithm proposed does not require any prior knowledge of primary user signals or noise in the systems, and can sense modulated signals under very low SNR. Simulation results are provided to verify the performance of the algorithm proposed under a low SNR and noise fluctuation. Compared with the maximum and minimum eigenvalue (MME) algorithm, frequency domain autocorrelation-based (FD-AC) algorithm and statistical knowledge autocorrelation-based (SKAB) algorithm, it improves about 4 dB margin in SNR.
Highlights
Due to the explosive growth of wireless devices and services, the scarcity of spectrum resources has become more and more serious
SYMMETRIC PEAKS-BASED SPECTRUM SENSING ALGORITHM we describe the spectrum sensing algorithm, which is based on the symmetric peaks of the cyclic autocorrelation function
According to the cyclic autocorrelation property of the modulated signal, a novel spectrum sensing algorithm based on symmetric peaks is proposed
Summary
Due to the explosive growth of wireless devices and services, the scarcity of spectrum resources has become more and more serious. The energy detection algorithm [3] is a widely used non-correlation detection algorithm It does not require any prior information of the PU signal, and has low computational complexity. The spectrum sensing performance of the energy detection algorithm is poor under a low SNR and noise fluctuation. Li et al proposed other spectrum detection algorithms based on the generalized likelihood ratio [12] and the signal information entropy [13], which improve the effect of noise uncertainty on spectrum sensing performance. We focus on spectrum sensing under the low SNR and noise fluctuation and propose a symmetric peaks-based spectrum sensing (SPS) algorithm for modulated signals.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
