Related Experiment Video
Updated: May 26, 2025

04:54
Author Spotlight: A Stable Phantom Material for Optical and Acoustic Imaging
Published on: June 16, 2023
2.7K
Orthogonal time-frequency space modulation for underwater mobile acoustic communications
Yukang Xue1, Xiyuan Zhu1, Y Rosa Zheng1
1Department of Electrical and Computer Engineering, Lehigh University, Bethlehem, Pennsylvania 18015, USA.
The Journal of the Acoustical Society of America
|February 21, 2025
Summary
A new turbo decision feedback equalizer and decoder (TDFED) improves underwater acoustic communications. This orthogonal time-frequency space (OTFS) system excels in challenging multipath and Doppler conditions.
Area of Science:
- Underwater acoustic communications
- Signal processing for wireless systems
Background:
- Underwater mobile acoustic communication channels face severe multipath and Doppler effects.
- Existing orthogonal frequency division modulation (OFDM) and single-carrier coherent modulation (SCCM) struggle with these channel impairments.
Purpose of the Study:
- To propose a novel turbo decision feedback equalizer and decoder (TDFED) for orthogonal time-frequency space (OTFS) systems.
- To enhance the performance of underwater mobile acoustic communications under challenging channel conditions.
Main Methods:
- Developed a time-domain TDFED for OTFS, utilizing feedforward and feedback filters.
- Implemented a low-complexity channel estimation in the delay-Doppler domain.
- Designed practical OTFS modulation for acoustic transmission (115 kHz center frequency, 11.5 ksps symbol rate).
Main Results:
- The proposed OTFS receiver demonstrated reduced accuracy requirements for Doppler compensation compared to SCCM and OFDM.
- The TDFED algorithm achieved a significantly better bit error rate (BER) in the presence of long multipath fading and severe Doppler shifts.
- Experimental results from lake tests validated the effectiveness of the proposed OTFS system.
Conclusions:
- The novel TDFED for OTFS is highly effective for underwater mobile acoustic communications.
- This approach offers superior performance over existing methods in mitigating multipath and Doppler effects.
- The study validates the practical applicability of OTFS in challenging underwater environments.
Related Concept Videos
Properties of Fourier Transform I
154
The application of Fourier Transform properties in radio broadcasting is multifaceted, enabling significant advancements in the way signals are transmitted and received. Key areas where these properties are utilized include simultaneous multi-channel transmission, audio clip speed adjustments, live broadcast delays for different time zones, audio frequency adjustments, and signal demodulation.
In radio broadcasting, multiple audio signals often need to be transmitted simultaneously. The Fourier...
In radio broadcasting, multiple audio signals often need to be transmitted simultaneously. The Fourier...
154
Properties of Fourier Transform II
155
The Fourier Transform (FT) is an essential mathematical tool in signal processing, transforming a time-domain signal into its frequency-domain representation. This transformation elucidates the relationship between time and frequency domains through several properties, each revealing unique aspects of signal behavior.
The Frequency Shifting property of Fourier Transforms highlights that a shift in the frequency domain corresponds to a phase shift in the time domain. Mathematically, if x(t) has...
The Frequency Shifting property of Fourier Transforms highlights that a shift in the frequency domain corresponds to a phase shift in the time domain. Mathematically, if x(t) has...
155
Sound Waves: Interference
3.7K
Sound waves can be modeled either as longitudinal waves, wherein the molecules of the medium oscillate around an equilibrium position, or as pressure waves. When two identical waves from the same source superimpose on each other, the combination of two crests or two troughs results in amplitude reinforcement known as constructive interference. If two identical waves, that are initially in phase, become out of phase because of different path lengths, the combination of crests with troughs...
3.7K
Wave Parameters
7.6K
The simplest mechanical waves are associated with simple harmonic motion and repeat themselves for several cycles. These simple harmonic waves can be modeled using a combination of sine and cosine functions. Consider a simplified surface water wave that moves across the water's surface. Unlike complex ocean waves, in surface water waves, water moves vertically, oscillating up and down, whereas the disturbance of the wave moves horizontally through the medium. If a seagull is floating on the...
7.6K
Echo
485
The human ear cannot distinguish between two sources of sound if they happen to reach within a specific time interval, typically 0.1 seconds apart. More than this, and they are perceived as separate sources.
Imagine the sound is reflected back to the ears. Assuming that the source is very close to the human, the difference between hearing the two sounds—the emitted sound and the reflected sound—may be more than the minimum time for perceiving distinct sounds. If this is the case,...
Imagine the sound is reflected back to the ears. Assuming that the source is very close to the human, the difference between hearing the two sounds—the emitted sound and the reflected sound—may be more than the minimum time for perceiving distinct sounds. If this is the case,...
485
Discrete-Time Fourier Series
209
The Discrete-Time Fourier Series (DTFS) is a fundamental concept in signal processing, serving as the discrete-time counterpart to the continuous-time Fourier series. It allows for the representation and analysis of discrete-time periodic signals in terms of their frequency components. Unlike its continuous counterpart, which utilizes integrals, the calculation of DTFS expansion coefficients involves summations due to the discrete nature of the signal.
For a discrete-time periodic signal x[n]...
For a discrete-time periodic signal x[n]...
209

