Spectrum Sensing Based on Novel Blind Pilot Detection Algorithm
Hsiao‐Chun Wu, Yu Bai, Kun Yan, Xiangli Zhang, Yiyan Wu · 2018
In this paper, we attempt to explore a new spectrum-sensing scheme, which involves a novel robust pilot-detection mechanism. Conventional signal (pilot) detection approaches rely on sampling the signal time-waveform or the corresponding frequency-spectrum. These approaches are seriously restricted to temporal variations and high noise-levels. We propose a new paradigm to transform the original received-signal waveform to the power spectrum and then the ultimate probabilistic function. Thus robust signal processing method such as clustering can be utilized to lead to the better pilot-detection performance of frequency-modulation (FM) broadcasted signals. To demonstrate the performance of our proposed pilot-tone detection and pilot-frequency estimation scheme, the corresponding Monte Carlo simulation results are compared with the conventional spectral-difference detector. Our proposed new pilot-tone detection and pilot-frequency estimation scheme lead to a significant performance margin compared to the conventional method, especially in low signal-to-noise ratios.