SVD-Based Signal Detector for Cognitive Radio Networks

This paper examines the implementation of the Singular Value Decomposition (SVD) method to detect the presence of wireless signal. The method is used to find the maximum and minimum eigenvalues. We simulated the algorithm using common digital signal in wireless communication namely rectangular pulse shape, raised cosine and root-raised cosine to test the performance of the signal detector. The SVD-based signal detector was found to be more efficient in sensing signal without knowing the properties of the transmitted signal. The execution time is acceptable compared to the favorable energy detection. The computational complexity of SVD-based detector is medium compared to the energy detector. The algorithm is suitable for blind spectrum sensing where the properties of the signal to be detected are unknown. This is also the advantage of the algorithm since any signal would interfere and subsequently affect the quality of service (QoS) of the IEEE 802.22 connection. Furthermore, the algorithm performed better in the low signal-to-noise ratio (SNR) environment.