Research and FPGA implementation of spectrum sensing algorithm based on fractional lower order covariance spectrum

Abstract

α stable distribution model is used to describe the non-Gaussian noise of the cognitive communication system based on the theoretical study of the spectrum sensing problem of the primary user in the case of non-Gaussian noise. A perceptual method based on fractional lower order covariance is given. Fractional lower order covariance spectrum is used to estimate the primary user signals under α stable distributed noise, which solves the problem of failure of the traditional power spectrum estimation performance under non-Gaussian noise. On the basis of the characteristics of the FPGA, the algorithm is further optimized, and the sensing system based on the algorithm is designed and implemented on the FPGA. The system uses FPGA to generate QPSK signal with center frequency of 25 MHz, bandwidth of 12.5 MHz and α stable distributed noise with characteristic index of 1 as the primary user signal. The corresponding digital signal processing module is designed and verified in this system. The sensing method based on the fractional lower order covariance can effectively detect the presence of the primary signal from the α stable distributed noise. The system is stable and portable, and it is suitable for different primary user spectrum detection schemes to be implemented and verified on this system.

Keywords

• spectrum sensing
• α stable distribution
• fractional lower order covariance spectrum
• FPGA