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

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arxiv 2406.06024 v1 pith:IGBU436A submitted 2024-06-10 eess.SP cs.ITmath.IT

Jinu Jayachandran , Muhammad Ubadah , Saif Khan Mohammed , Ronny Hadani , Ananthanarayanan Chockalingam , Robert Calderbank This is my paper · ORCID
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keywords zak-otfssensingsystemturbobaselinechannelcommunicationcondition
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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.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. A Gaussian-Sinc Pulse Shaping Filter for Zak-OTFS

    cs.IT 2025-02 conditional novelty 6.0 of 10

    A Gaussian-sinc pulse shaping filter for Zak-OTFS combines sinc nulls with Gaussian sidelobe suppression and is reported to improve BER by 4 to 6 dB in simulations.

  2. Differential Communication in Channels with Mobility and Delay Spread using Zak-OTFS

    eess.SP 2025-07 conditional novelty 5.0 of 10

    In Zak-OTFS, the cross-ambiguity of received and transmitted random data is approximately the channel, so detected data can replace periodic pilots and enable pilot-free differential detection.

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