Frequency spectrum analysis of compressed sampling datum based on modulated wideband converter

Abstract

In order to reduce the computational complexity of frequency spectrum analysis, we aim to investigate spectrum directly from compressed sampling datum based on Modulated Wideband Converter (MWC) principle without using sparse reconstruction operation. Due to better performance of processing multiband signal, MWC is the most successful architecture of compressed sensing (CS) techniques in Analog-to-Information Conversion (AIC). This MWC model is extended to digital domain in order to construct a novel architecture of wideband digital receiver in this paper. A complex input signal is satisfied to be fed into the digital receiver. Then the minimum number M of compressed sampling branches is 2 N compared to 4N of MWC, with N sparse level in frequency domain of input signal. According to the principle that the signal modulated by periodic pseudo random sequence can obtain linear combination spectrum of periodic shifted copies and each subband already contains all spectrum information of input signal, spectrum information can be analyzed from compressed sampling datum directly. Simulations of testing cross-subband signals and inband signals are conducted and validate the efficiency of the proposed approach.