Channel-Aware OTFS Modulation for Underwater Acoustic Communications

From Theoretical Analysis to Experimental Validation

Doctoral Thesis (2026)
Author(s)

I. Van der Werf (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

R.C. Hendriks – Promotor (TU Delft - Electrical Engineering, Mathematics and Computer Science)

R. Heusdens – Promotor (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Research Group
Signal Processing Systems
DOI related publication
https://doi.org/10.4233/uuid:fae4dda8-23b9-4b1e-aef8-08e19ce81094 Final published version
More Info
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Publication Year
2026
Language
English
Defense Date
27-10-2026
Awarding Institution
Delft University of Technology
Research Group
Signal Processing Systems
ISBN (print)
978-94-6563-049-6
ISBN (electronic)
978-94-6518-431-9
Page Views
11
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Abstract

Underwater wireless communication is a cornerstone of modern marine exploration, infrastructure maintenance, and naval operations. While terrestrial systems rely on electromagnetic radio-frequency (RF) waves, these are impractical underwater due to rapid attenuation. Consequently, underwater communication typically utilizes acoustic pressure waves, which can propagate over tens of kilometers. However, underwater acoustic (UWA) communication is characterized by limited bandwidth, high latency due to slow propagation, and severe distortions from multipath-induced delay and motion-induced Doppler spreads. This dissertation investigates the design of an UWA system that is both analytically tractable and sufficiently flexible to adapt to these volatile conditions in real time.

The research begins by examining state-of-the-art communication schemes in both UWA and terrestrial domains. A key theoretical contribution is the demonstration that two prominent schemes, developed independently in their respective fields, are mathematically equivalent. Further analysis of the time-frequency signal structure reveals that the benefit of these schemes stems from the fact that information is spread across both time and frequency.

A central challenge addressed is the trade-off between training and data transmission. By proposing a novel training design, this dissertation demonstrates a 50% reduction in training overhead compared to conventional designs without sacrificing estimation accuracy. Finally, to bridge the gap between theory and application, a channel-aware adaptation protocol is introduced. This allows the system to optimize parameters in-situ, ensuring a robust link. The approach was validated through synthetic simulations, channel replay, and real-world experiments.

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