Stochastic resonance for spectrum sensing of multi-carrier modulated waveforms

Abstract

Spectrum sensing has received abundant attention from the research community. However, with sensing scenarios becoming increasingly complex, existing spectrum sensing schemes can hardly meet the demand for fast, accurate spectrum sensing, particularly in the very low signal-to-noise ratio (SNR) range, without dramatically increasing system complexity and the need for precise information about signal and noise. Furthermore, the widespread adoption of multicarrier modulation in various existing and evolving standards is driving efforts to develop a robust and practical solution for multicarrier signal spectrum sensing. The main challenges identified in lieu of changing spectrum scenarios are detection in low SNR, high accuracy, low computational and sample complexity, and possible operation without the knowledge of the primary user (PU) signal and channel. Stochastic Resonance (SR) is a phenomenon in which a signal too weak to cross the detection threshold becomes detectable in a nonlinear system with the addition of noise. This research considers the application of SR to sense multi-frequency/multi-carrier signals. The effect of the SR receiver has never been verified for multi-carrier signals, which is a popular modulation system in various existing and evolving standards. The thesis provides an understanding of how and why the SR effect for multi-frequency signals differs from the SR effect for single frequency signals. Special features such as ghost resonance, multi-resonance and doubly SR are demonstrated with simulations. A novel method to identify ghost resonance is proposed and the relationship of noise intensity and frequencies of the driving signal is derived. SR for multi-frequency signals is quantified in terms of the SNR. In the presented research, SR is used as a pre-processing technique to enhance SNR prior to the detector, which significantly improves spectrum sensing performance. The two main contributions in this part of the research are (i) A novel algorithm for dynamic determination of SR system parameters and noise intensity, which results in maximum SNR; (ii) An SR-based sensing method particularly tailored to give near-optimal performance for multi-carrier signals by using the multi-taper spectral estimate (MTSE) method. A simple Fourier transform-based method is also evaluated as a computationally light alternative to MTSE. The FFT-based method combined with (i) provides near-optimal performance for single-carrier modulated schemes. The performance is evaluated in low SNR, flat/frequency selective fading, iii shadowing, interference and time/frequency offset. The results show that by using SR pre-processing, the performance of energy-based detection (ED) can be significantly improved. The proposed method is also evaluated in cooperative sensing scenarios. The results show that the proposed SR-ED with a basic cooperative mechanism can match the performance of ED-based cooperative sensing with optimal fusion. The proposed method has several distinctive features including low latency, high accuracy, reasonable computational complexity, robustness to low SNR, robustness to flat/frequency selective fading, robustness to noise/channel uncertainty. It also requires no prior knowledge of the PU signal.