Cognitive radio is a wireless communication technology that seeks to increase communication efficiency by dynamically changing transmission parameters in response to actively monitored environmental factors. This communication device relies on spectrum sensing, the task of assessing spectrum usage and the presence of primary users in the geographical area. Current technologies fail to adequately assess spectrum usage despite uncertain knowledge of channel noise characteristics. This technology is a spectrum sensing scheme based on the K-S test, a non-parametric statistical method for comparing continuous, one-dimensional probability distributions for goodness of fit. This technology could be used to design cognitive radio wireless networks that can handle multiple users with improved performance and robustness to noise.
This technology is significantly faster and more robust than available algorithms designed for spectrum detection. Provided with only a short sequence of noise samples, the technology was demonstrated to have a robust signal detection and performance even in the presence of noise. Furthermore, the simulations also demonstrated the technology had improved ability to channel uncertainty and non-Gaussian noise over existing spectrum sensing methods such as energy detectors, feature-based spectrum sensing, and eigenvalue-based methods.
The increased speed and robustness of this technology has been successfully tested in software simulations of multipath fading multiple-input multiple-output (MIMO) channels.
Tech Ventures Reference: IR M11-047
