基于分数低阶协方差谱的频谱感知算法研究及其FPGA实现

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

在对非高斯噪声情况下主用户频谱感知问题的理论研究之上,采用α稳定分布模型描述认知通信系统的非高斯噪声,给出了一种基于分数低阶协方差的感知方法,并采用分数低阶协方差谱对α稳定分布噪声下的主用户信号进行了谱估计,较好地解决了在非高斯噪声情况下传统的功率谱估计性能失效的问题。在此基础上针对FPGA的特性,进一步优化了算法,在FPGA上设计并实现了基于该算法的感知系统。系统利用FPGA产生中心频率为25 MHz、带宽为12.5 MHz的QPSK信号和特征指数为1的α稳定分布噪声作为主用户信号,设计相应的数字信号处理模块,并在此系统中验证了基于分数低阶协方差的感知方法能够有效地从α稳定分布噪声中检测出主信号的存在。该系统运行稳定,可移植性强,适用于不同的主用户频谱检测方案在此系统上进行实现与验证。

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.