SNR-Adaptive Ranging Waveform Design Based on Ziv-Zakai Bound Optimization

TL;DR

This paper introduces an SNR-adaptive waveform design for precise wireless ranging using the Ziv-Zakai bound, optimizing performance across different noise levels and highlighting the importance of detection probability in low-SNR conditions.

Contribution

It proposes a novel waveform design algorithm based on the Ziv-Zakai bound that adapts to SNR, providing theoretical guarantees of optimality in ranging performance.

Findings

Detection probability is more critical than resolution at low SNR.

The proposed design outperforms traditional high-SNR optimized waveforms.

Numerical results validate the effectiveness of the SNR-adaptive approach.

Abstract

Location-awareness is essential in various wireless applications. The capability of performing precise ranging is substantial in achieving high-accuracy localization. Due to the notorious ambiguity phenomenon, optimal ranging waveforms should be adaptive to the signal-to-noise ratio (SNR). In this letter, we propose to use the Ziv-Zakai bound (ZZB) as the ranging performance metric, as well as an associated waveform design algorithm having theoretical guarantee of achieving the optimal ZZB at a given SNR. Numerical results suggest that, in stark contrast to the well-known high-SNR design philosophy, the detection probability of the ranging signal becomes more important than the resolution in the low-SNR regime.