On the Estimation of Nonrandom Signal Coefficients from Jittered Samples

TL;DR

This paper addresses estimating bandlimited signal parameters from jittered and noisy samples, deriving bounds, developing an EM algorithm, and demonstrating improved jitter tolerance and potential ADC power savings.

Contribution

It introduces an EM-based estimator for jittered samples, analyzes its performance, and shows it outperforms linear methods in jitter robustness.

Findings

EM algorithm approaches maximum likelihood estimation.

Proposed method tolerates higher jitter levels.

Potential for reducing ADC power consumption.

Abstract

This paper examines the problem of estimating the parameters of a bandlimited signal from samples corrupted by random jitter (timing noise) and additive iid Gaussian noise, where the signal lies in the span of a finite basis. For the presented classical estimation problem, the Cramer-Rao lower bound (CRB) is computed, and an Expectation-Maximization (EM) algorithm approximating the maximum likelihood (ML) estimator is developed. Simulations are performed to study the convergence properties of the EM algorithm and compare the performance both against the CRB and a basic linear estimator. These simulations demonstrate that by post-processing the jittered samples with the proposed EM algorithm, greater jitter can be tolerated, potentially reducing on-chip ADC power consumption substantially.