Stochastically resonant spectrum sensing for white space communications: Dynamic spectrum access and intelligent radios and networks

This paper proposes and investigates Stochastically Resonant Spectrum Sensing (SRSS) in order to expedite Dynamic Spectrum Access and TV White Space (TVWS) communications. SRSS adds noise to a signal in order to enhance its Signal-to-Noise Ratio (SNR) and can be useful in sensing and detecting weak signals, e.g. weak Primary User or even Secondary User activity in TVWS. We demonstrate that SR is a useful Spectrum Sensing technique and can improve SNRs by ~8-10 dB using MATLAB simulations. Typically, SRSS uses only Additive SR Noise and we include and also investigate Multiplicative SR Noise effects, showing that in certain instances the latter can also improve SNRs by ~2 dB. We compare the Additive versus the combined Additive and Multiplicative cases using Uniform and Normal/Gaussian distributions and present our results. Our ultimate goal is to include SRSS in an IEEE/DySPAN-SC 1900*. Standards based Interference Managing Ontological Cognitive Radio, Intelligent Radio or Policy Based Radio for Ad-Hoc and Heterogeneous i.e. Composite Wireless Networks.