Non-linear space-time Kalman filter for cooperative spectrum sensing in cognitive radios

A cooperative spectrum-sensing problem for a cognitive radio (CR) system is investigated, where CR users collaborate to sense and track the primary users’ (PUs) activities in frequency-selective fading channels. To sense PUs activities, channel gain estimation is performed by CRs through space–time extended Kalman filtering (STEKF). The STEKF method captures the channel gain from any point in space to each CR at each frame for a specific range of frequencies. The proposed channel gain tracking enables CRs to detect the transmit power, location and the number of active subcarriers of each PU via a time spatial weighted non-negative Lasso (TSWNL) algorithm. The TSWNL exploits the sparsity of the PUs activities in a geographical area to track PUs activities in frequency-selective fading channels. Numerical results indicate that the proposed spectrum sensing based on STEKF significantly improves the performance of CRs in tracking of PUs activities.