Zak-OTFS and Turbo Signal Processing for Joint Sensing and Communication

TL;DR

This paper introduces a turbo signal processing approach for Zak-OTFS systems that enables joint sensing and communication, matching the performance of separate sensing and data transmission systems.

Contribution

It proposes a novel turbo decoding method that integrates sensing and communication within the same Zak-OTFS subframe, improving efficiency.

Findings

Turbo decoding matches baseline BER performance

Joint sensing and communication within one subframe is feasible

Zak-OTFS I/O relation is predictable under certain conditions

Abstract

The Zak-OTFS input/output (I/O) relation is predictable and non-fading when the delay and Doppler periods are greater than the effective channel delay and Doppler spreads, a condition which we refer to as the crystallization condition. The filter taps can simply be read off from the response to a single Zak-OTFS pilot pulsone, and the I/O relation can be reconstructed for a sampled system that operates under finite duration and bandwidth constraints. In previous work we had measured BER performance of a baseline system where we used separate Zak-OTFS subframes for sensing and data transmission. In this Letter we demonstrate how to use turbo signal processing to match BER performance of this baseline system when we integrate sensing and communication within the same Zak-OTFS subframe. The turbo decoder alternates between channel sensing using a noise-like waveform (spread pulsone) and recovery of data transmitted using point pulsones.