Blind primary user identification in MIMO cognitive networks

Early detection of primary users presence is one of the most important tasks for cognitive communication. Also, in cognitive settings cognitive nodes may receive signals from primary users and from other cognitive users simultaneously. For such scenario, we propose primary user signal detection using modulation class identification method. We consider multiple transmit and multiple receive antennas for cognitive nodes. We employ Artificial Neural Network (ANN) for the modulation identification purpose. The proposed algorithm works as higher order moments and cumulants are calculated from the received signal samples at each of the receiving branches of cognitive nodes. After this step, these features are fed to the ANN to determine the presence of primary users. Final identification decision is drawn using the decision from all receiving branches. We also present numerical results of our algorithm and compare these results with the theoretical results of the energy detection algorithm.