On the beamforming and blind interference threshold estimation in underlay cognitive system

This paper aims at providing a solution for blind interference threshold estimation in an underlay cognitive network. Unlike the traditional methods that mainly depend on pre-cooperation between primary and secondary users to settle on a predefined threshold. For threshold estimation, blind detection of modulation and signal-to-noise ratio (SNR) are used. For the sake of beamforming, several localization algorithms are compared to settle on best one for cognitive environment. Beamforming algorithms as Linear Constraint Minimum Variance and Minimum Variance Distortion less are compared. Just nulling the primary user after knowledge of its location is discussed against working under interference threshold.