Quantized Signal Recovery with Interference via Parametrized Look-Up Tables

Abstract

Efficient all-digital post-correction of low-resolution analog-to-digital converters can be achieved by using Look-Up Tables (LUTs). The performance of a LUT can be optimized by incorporating a parametric model for the expected input signal, noise level, and interference signals. We evaluate three analytical estimators for integration with parametrized LUTs, especially with applications to low-resolution, non-linear, or wideband quantizers. We also propose several approximations to improve tractability of the estimation problem for Phase-Shift Keyed input signals and Linear Frequency Modulated interference signals. Simulated results validate the ability of our estimator to recover the instantaneous value of the desired input signal in real-time with a high degree of accuracy. This includes cancellation of harmonic distortion that aliases into the desired signal bandwidth from front-end saturation due to high-power out-of-band interference. Our estimators are shown to achieve a significant gain over conventional linear-filtering techniques while also being robust to changes in input parameters, non-linear quantizers, and time-variant interference sources. For a tone input quantized to 3 bits and estimated with a fixed 12-tap model order we achieve $>$10 dB improvement in Mean Square Error and $>$20 dBc improvement in Spurious-Free Dynamic Range.