An Algorithm to Compensate the Effects of Spurious PLL Tones in Spectrum Sensing Architectures

TLDR: An algorithm that uses a Fourier Transform block (a typical component in spectrum sensing architectures) to estimate the sampling errors from the spurious sidebands is proposed and computer simulations are included to show that the proposed solution can remove the spuriousSidebands and improve the detection performance.

Abstract: In a nonideal PLL circuit, leakage of the reference signal into the control line produces spurious tones. When the distorted PLL signal is used as a sampling clock to an analog-to-digital converter (ADC), it creates spurious sidebands in the sampled data as well. In spectrum sensing applications, the presence of spurious sidebands can lead to false detection of signals in otherwise empty channels. To remove the spurious sidebands, we first estimate the distortions to the sampled data and then compensate the data in the digital domain. To reduce hardware complexity and computation cost, we propose an algorithm that uses a Fourier Transform block (a typical component in spectrum sensing architectures) to estimate the sampling errors from the spurious sidebands. We also analyze the effects of the spurious sidebands on spectrum sensing. Computer simulations are included to show that the proposed solution can remove the spurious sidebands and improve the detection performance.