Enhanced energy detector via algebraic approach for spectrum sensing in cognitive radio networks

This paper deals with spectrum sensing techniques used to efficient utilization of limited spectrum resource. The most used technique is the energy detector as it is the simplest one for real time implementation and performs well for high SNR. This paper is concerned with this well known method and introduces an enhanced energy detector, in order to enhance its performance in low SNR. The proposed detector is based on the algebraic approach used for spike location, to make the detection more robust in a noisy environment. The proposed system model introduces an algebraic preprocessing bloc to attenuate the noise effect and enhance the detector performance at lower SNR. The detection is achieved by a second bloc that implements the conventional energy detection method. Simulation results, performed on DVB-T signals in additive Gaussian noisy context, show that the proposed detector performs much better than the conventional energy detector.