Sampling and Distortion Tradeoffs for Bandlimited Periodic Signals

TL;DR

This paper analyzes the optimal sampling strategies and distortion tradeoffs for Gaussian bandlimited periodic signals, revealing when uniform or nonuniform sampling is optimal and providing bounds for intermediate rates.

Contribution

It characterizes optimal sampling locations and filters for minimizing distortion, and compares uniform and nonuniform sampling strategies across different rates.

Findings

Nonuniform sampling outperforms uniform sampling at low rates.

No pre-sampling filter is needed for optimal distortion.

Uniform sampling is optimal above the Nyquist rate.

Abstract

In this paper, the optimal sampling strategies (uniform or nonuniform) and distortion tradeoffs for Gaussian bandlimited periodic signals with additive white Gaussian noise are studied. Our emphasis is on characterizing the optimal sampling locations as well as the optimal pre-sampling filter to minimize the reconstruction distortion. We first show that to achieve the optimal distortion, no pre-sampling filter is necessary for any arbitrary sampling rate. Then, we provide a complete characterization of optimal distortion for low and high sampling rates (with respect to the signal bandwidth). We also provide bounds on the reconstruction distortion for rates in the intermediate region. It is shown that nonuniform sampling outperforms uniform sampling for low sampling rates. In addition, the optimal nonuniform sampling set is robust with respect to missing sampling values. On the other hand, for the sampling rates above the Nyquist rate, the uniform sampling strategy is optimal. An extension of the results for random discrete periodic signals is discussed with simulation results indicating that the intuitions from the continuous domain carry over to the discrete domain. Sparse signals are also considered, where it is shown that uniform sampling is optimal above the Nyquist rate.