Low-Complexity Pilot-Aided Doppler Ambiguity Estimation for OTFS Parametric Channel Estimation

TL;DR

This paper introduces a low-complexity pilot-aided method for detecting and compensating Doppler ambiguity in OTFS channels, crucial for high-mobility scenarios like LEO satellite communications, improving accuracy without high computational costs.

Contribution

It presents a novel two-stage estimator leveraging phase differences for Doppler ambiguity detection and compensation in OTFS, with analysis of pilot arrangements and reduced complexity.

Findings

Effectively eliminates ambiguity-induced error floors

Achieves BER and NMSE comparable to exhaustive search methods

Maintains low computational complexity similar to standard MLE

Abstract

Orthogonal Time Frequency Space (OTFS) modulation offers robust performance in high-mobility scenarios by transforming time-varying channels into the delay-Doppler (DD) domain. However, in high-mobility environment such as emerging 5G Non-Terrestrial Networks (NTN), the extreme orbital velocities of Low Earth Orbit (LEO) satellites frequently cause the physical Doppler shifts to exceed the fundamental grid range. This Doppler ambiguity induces severe model mismatch and renders traditional MLE channel estimators ineffective. To address this challenge, this paper proposes a novel low-complexity pilot-aided Doppler ambiguity detection and compensation framework. We first mathematically derive the OTFS input-output relationship in the presence of aliasing, revealing that Doppler ambiguity manifests itself as a distinct phase rotation along the delay dimension. Leveraging this insight, we developed a two-stage estimator that utilizes pairwise phase differences between pilot symbols to identify the integer ambiguity, followed by a refined Maximum Likelihood Estimation (MLE) for channel recovery. We investigate two pilot arrangements, Embedded Pilot with Guard Zone (EP-GZ) and Data-Surrounded Pilot (DSP), to analyze the trade-off between interference suppression and spectral efficiency. Simulation results demonstrate that the proposed scheme effectively eliminates the error floor caused by ambiguity, achieving Bit Error Rate (BER) and Normalized Mean Square Error (NMSE) performance comparable to the exhaustive search benchmark while maintaining a computational complexity similar to standard MLE.