Compressed Sensing With Nonlinear Analog Mapping in a Noisy Environment

We propose a low delay and low complexity sensor system based on the combination of Shannon–Kotel'nikov mapping and compressed sensing (CS). The proposed system uses nonlinear analog mappings on the CS measurements to increase their immunity against channel noise. Numerical results show that the proposed purely-analog system outperforms the state-of-the-art purely CS systems in terms of signal-to-distortion ratio. In addition to sparsity knowledge, we use a statistical characterization of the observed signal to further improve system performance.