Jitter characterization of incoherently sub-sampled high-speed digital signals

A jitter characterization approach for incoherently sub-sampled high-speed digital signals using back-end signal processing algorithms is presented. Signal sub-sampling is used to increase the effective sampling rate of the digitizer used for data acquisition while incoherent sampling is utilized to simplify the data acquisition hardware. Algorithms for signal clock recovery and waveform reconstruction from the acquired data are developed in this research. The algorithms utilize peak identification of the sampled signal spectrum and the sparsity of the reconstructed waveform in the frequency domain as decision criteria for accurate signal reconstruction. To quantize the jitter value of such a reconstructed waveform, a wavelet based denoising method is used to generate a self-reference signal against which zero-crossing times are compared to generate jitter statistics. In addition, the data dependent jitter components can be differentiated from the original jitter by analyzing zero-crossing discrepancies of the self-reference signal.