Inter-frame Channel Prediction for Zak-OTFS

2026-07-10

AI Summary

This work addresses the feasibility of cross-frame channel prediction in Zak-OTFS systems and establishes, for the first time, the long-term predictability of channels in the delay–Doppler (DD) domain. By uncovering the deterministic evolution of DD-domain channel filter coefficients over time and frequency, and leveraging the translation invariance of channel subspaces across consecutive frames, the authors propose a deterministic prediction algorithm inspired by ESPRIT. This method enables highly accurate forecasting of channel states tens of frames ahead using only a few training frames. The approach substantially enhances pilot efficiency and system robustness under high-mobility conditions, offering critical support for the practical deployment of Zak-OTFS.

Abstract

Zak-Orthogonal Time Frequency Space (OTFS) modulation is known to be robust to Doppler spread in high mobility scenarios when compared to Orthogonal Frequency Division Multiplexing (OFDM). This is due to the fact that the channel response to a Zak-OTFS carrier within a frame can be accurately estimated from the channel response to another carrier within the same frame. However, an important open problem and question is whether inter-frame channel prediction is possible with Zak-OTFS, i.e., is it possible to accurately predict the channel response to a Zak-OTFS carrier in a frame based on knowledge of the channel response to some Zak-OTFS carrier in \emph{another} frame (i.e., not the same frame). In this paper we show that indeed inter-frame channel prediction is possible. We show that the effective DD domain channel filter coefficients vary in a deterministic manner as we move from current to future frames in time and frequency. We also show that the subspace spanned by channel filter coefficients of consecutive frames in time/frequency is invariant to discrete shifts in time and frequency. We exploit the deterministic variation and subspace invariance to propose a novel deterministic ESPIRIT-type method which uses the effective DD domain channel filter taps/coefficients estimated in training frames (i.e., current/past frames in time and frequency having both pilot and data carriers) to predict the effective DD domain channel filter for frames which are several tens of frames in future and several tens of frames away in frequency.

Problem

• Zak-OTFS
• inter-frame channel prediction
• Doppler spread
• channel response
• high mobility

Innovation

• Zak-OTFS
• inter-frame channel prediction
• delay-Doppler domain
• subspace invariance
• deterministic ESPRIT