Frequency Locator Polynomial for Wideband Sparse Spectrum Sensing With Multichannel Subsampling

Abstract

BigBand is a technique for wideband spectrum sensing (WSS) that can capture gigahertz of sparse spectrum in real time by using shifted multiple channels without sampling the signal at GS/s. In this paper, we focus on enforcing BigBand with the proposed improved algorithm, namely, AD-BigBand, for efficient and robust computation. AD-BigBand converts the nonlinear process (locating frequency and computing the spectrum value) of sparse WSS into two steps of solving linear equations. In particular, we define an $r$ -degree frequency locator polynomial to rapidly locate nonzero frequencies. The computing complexity of the proposed method decreases from $O(K{\log ^2}K ({{{n\log K} \over K}})^{\log K})$ of shifted sampling based BigBand to $O(K{\log ^2}K)$ , where the $K$ -sparse signals of bandwitdth $n$ are subsampled with arithmetic time-shifted sensing channels. We implement AD-BigBand on a commercial four-channel acquisition card. Experimental results show that AD-BigBand improves the WSS capabilities and exhibits higher processing speed and lower error spectrum construction rate than BigBand, especially in the case of relative low signal-to-noise ratio.