Underwater Acoustic Communication Research Articles

Analysis of Transient Thermoacoustic Characteristics and Performance in Carbon Nanotube Sponge Underwater Transducers

Recent advancements in marine technology have highlighted the urgent need for enhanced underwater acoustic applications, from sonar detection to communication and noise cancellation, driving the pursuit of innovative transducer technologies. In this paper, a new underwater thermoacoustic (TA) transducer made from carbon nanotube (CNT) sponge is designed to achieve wide bandwidth, high energy conversion efficiency, simple structure, good transient response, and stable sound response, utilizing the TA effect through electro-thermal modulation. The transducer has potential application in underwater acoustic communication. An electro-thermal-acoustic coupled simulation for the open model, sandwich model, and encapsulated model is presented to analyze the transient behaviors of CNT sponge TA transducers in liquid environments. The effects of key design parameters on the acoustic performances of both systems are revealed. The results demonstrate that a short pulse excitation with a low duty cycle could greatly improve the heat dissipation of the encapsulated transducer, especially when the thermoacoustic response time becomes comparable to thermal relaxation time.

Suppression of effects of the synchronization error with adaptive down-conversion for underwater acoustic communication

In underwater acoustic communication, inaccurate synchronization can cause an incorrect estimation of the uniform Doppler shift and degrade the demodulation performance. In this paper, it is mathematically described how the inaccurate synchronization affects the demodulation procedure. Moreover, it is also shown theoretically that adaptive down-conversion, which has been proposed to suppress the effects of the nonuniform Doppler shift, reduces the degradation of the demodulation performance caused by the inaccurate synchronization. Furthermore, the improvement in the demodulation performance by the adaptive down-conversion is evaluated using experimental data. The demodulation results of the addition of intended synchronization errors clearly show that the adaptive down-conversion reduced the effects of the synchronization errors and improved the demodulation performance in the case of inaccurate synchronization.

MEMS flexible conformal hydrophone based on heterogeneous integration technology

PurposeHuman-induced marine environmental noise, such as commercial shipping and seismic exploration, is concentrated in the low-frequency range. Meanwhile, low-frequency sound signals can achieve long-distance propagation in water. To meet the requirements of long-distance underwater detection and communication, this paper aims to propose an micro-electro-mechanical system (MEMS) flexible conformal hydrophone for low-frequency underwater acoustic signals. The substrate of the proposed hydrophone is polyimide, with silicon as the piezoresistive unit.Design/methodology/approachThis paper proposes a MEMS heterojunction integration process for preparing flexible conformal hydrophones. In addition, sensors prepared based on this process are non-contact flexible sensors that can detect weak signals or small deformations.FindingsThe experimental results indicate that making devices with this process cannot only achieve heterogeneous integration of silicon film, metal wire and polyimide, but also allow for customized positions of the silicon film as needed. The success rate of silicon film transfer printing is over 95%. When a stress of 1 Pa is applied on the x-axis or y-axis, the maximum stress on Si as a pie-zoresistive material is above, and the average stress on the Si film is around.Originality/valueThe flexible conformal vector hydrophone prepared by heterogeneous integration technology provides ideas for underwater acoustic communication and signal acquisition of biomimetic flexible robotic fish.

Image Super Resolution-Based Channel Estimation for Orthogonal Chirp Division Multiplexing on Shallow Water Underwater Acoustic Communications.

Orthogonal chirp division multiplexing (OCDM) offers a promising modulation technology for shallow water underwater acoustic (UWA) communication systems due to multipath fading resistance and Doppler resistance. To handle the various channel distortions and interferences, obtaining accurate channel state information is vital for robust and efficient shallow water UWA communication. In recent years, deep learning has attracted widespread attention in the communication field, providing a new way to improve the performance of physical layer communication systems. In this paper, the pilot-based channel estimation is transformed into a matrix completion problem, which is mathematically equivalent to the image super-resolution problem arising in the field of image processing. Simulation results show that the deep learning-based method can improve the channel distortion, outperforming the equalization performed by traditional estimator, the performance of Bit Error Rate is improved by 2.5 dB compared to the MMSE method in OCDM system. At the 7.5 to 20 dB region, it achieves better bit error rate performance than OFDM systems, and the bit error rate is reduced by approximately 53% compared to OFDM when the SNR value is 20, which is very useful in shallow water UWA channels with multipath extension and severe time-varying characteristics.

Coverage Performance of Non-Lambertian Underwater Wireless Optical Communications for 6G Internet of Things

In medium- and short-range underwater application scenarios, thanks to the superior performance in transmission bandwidth, link latency, and security, underwater wireless optical communication (UWOC) is growing to be a promising complement to the mature underwater acoustic communication technique. In order to extend the future 6G Internet of Things (IOT) to various challenging and valuable underwater scenarios, the underwater spatial coverage and transmission performance has been actively discussed in typical seawater environments. However, almost all current works focus on underwater scenarios including light-emitting diode (LED) transmitters with well-known Lambertian optical beams and fail to characterize the scenarios adopting LED transmitters with distinctive non-Lambertian beam patterns. For addressing this limitation, in this article, the coverage performance of non-Lambertian UWOC for 6G is analyzed and illustrated. Furthermore, the switchable optical beam configuration scheme is proposed and estimated for UWOC. Numerical results illustrate that, compared with about 15.42 dB signal-to-noise ratio (SNR) fluctuation amplitude for UWOC with baseline Lambertian optical beam configuration, the corresponding SNR fluctuation amplitudes of UWOC based with two typical non-Lambertian optical beams are 8.71 dB and 24.60 dB. Furthermore, once the receiver depth is increased to 6.0 m, the SNR fluctuation amplitude for the above three UWOC coverage with distinct beam configuration could be reduced to 5.61 dB, 1.58 dB, and 10.33 dB, respectively.

Channel Prediction for Underwater Acoustic Communication: A Review and Performance Evaluation of Algorithms

Underwater acoustic (UWA) channel prediction technology, as an important topic in UWA communication, has played an important role in UWA adaptive communication network and underwater target perception. Although many significant advancements have been achieved in underwater acoustic channel prediction over the years, a comprehensive summary and introduction is still lacking. As the first comprehensive overview of UWA channel prediction, this paper introduces past works and algorithm implementation methods of channel prediction from the perspective of linear, kernel-based, and deep learning approaches. Importantly, based on available at-sea experiment datasets, this paper compares the performance of current primary UWA channel prediction algorithms under a unified system framework, providing researchers with a comprehensive and objective understanding of UWA channel prediction. Finally, it discusses the directions and challenges for future research. The survey finds that linear prediction algorithms are the most widely applied, and deep learning, as the most advanced type of algorithm, has moved this field into a new stage. The experimental results show that the linear algorithms have the lowest computational complexity, and when the training samples are sufficient, deep learning algorithms have the best prediction performance.

Channel Estimation for Underwater Acoustic Communications in Impulsive Noise Environments: A Sparse, Robust, and Efficient Alternating Direction Method of Multipliers-Based Approach

Channel estimation in Underwater Acoustic Communication (UAC) faces significant challenges due to the non-Gaussian, impulsive noise in ocean environments and the inherent high dimensionality of the estimation task. This paper introduces a robust channel estimation algorithm by solving an l1−l1 optimization problem via the Alternating Direction Method of Multipliers (ADMM), effectively exploiting channel sparsity and addressing impulsive noise outliers. A non-monotone backtracking line search strategy is also developed to improve the convergence behavior. The proposed algorithm is low in complexity and has robust performance. Simulation results show that it exhibits a small performance deterioration of less than 1 dB for Channel Impulse Response (CIR) estimation in impulsive noise environments, nearly matching its performance under Additive White Gaussian Noise (AWGN) conditions. For Delay-Doppler (DD) doubly spread channel estimation, it maintains Bit Error Rate (BER) performance comparable to using ground truth channel information in both AWGN and impulsive noise environments. At-sea experimental validations for channel estimation in Orthogonal Frequency Division Multiplexing (OFDM) systems further underscore the fast convergence speed and high estimation accuracy of the proposed method.

An integrated waveform design method for underwater acoustic detection and communication

AbstractIn recent years, the integrated system for underwater detection and communication (ISUDC) has become one of the important research directions. At present, the efficiency of the existing shared signals carrying communication information is low, and the synchronization performance needs to be further improved. So, this paper proposes an integrated waveform design scheme for ISUDC based on the carrier with good detection performance and binary phase shift differential keying (DBPSK). In this scheme, the signal with better underwater detection performance (e.g. Linear Frequency Modulation, LFM) is selected as the carrier, and DBPSK is used as the modulation mode to modulate the communication symbols into the carrier. However, the correlation of the detection signal will be destroyed. Thus, the down‐frequency detection signal (e.g. ngLFM) is superimposed into the signal to form a shared signal (LFM‐DBPSK‐ng, LDN). The detection performance, synchronization performance and communication performance of the shared signal are analyzed by ambiguity function, cross‐correlation and BER, respectively. In addition, according to the proposed scheme, the shared signal HFM‐DBPSK‐ng (HDN) is generated by using HFM as carrier. The comparative simulation experiments are carried out with the existing LFM‐BPSK signals. Experiments show that both LDN and HDN have better performance compared to the other shared signals, which proves the effectiveness of the integrated waveform design scheme for ISUDC proposed in this paper.

A sparse adaptive decision feedback equalization approach for the high data rate vertical underwater acoustic communication in deep sea

In underwater acoustic communication (UWAC) environments, multichannel decision feedback equalizer (MDFE) techniques combined with single carrier modulation schemes are widely employed to suppress multipath interference while adapting to time-varying channel response. While MDFE is a powerful technique, the estimation of the numerous filter taps is generally complex problem, and the numerically complexities can lead to the instability of solutions including the occurrence of the burst errors. In this study, we propose a method that introduces L1-norm regularization into the adaptive algorithm of MDFE, considering a sparse channel response environment in the vertical UWAC channel in deep-sea areas. We applied the proposed method to simulation and experimental data, comparing it with conventional methods. As a result, the proposed method demonstrated a clear improvement in bit error rate performance, obtaining sparse filter coefficient estimates and effectively suppressing burst errors.

Joint Equalization and Self-Interference Cancellation for Underwater Acoustic In-Band Full-Duplex Communication

Joint Equalization and Self-Interference Cancellation for Underwater Acoustic In-Band Full-Duplex Communication

Quantitative identification of causes of instrumental acoustic signal distortion in Global Navigation Satellite System-Acoustics Combination observations.

The Seafloor Geodetic Observation-Array (SGO-A), operated by the Japan Coast Guard, relies on the Global Navigation Satellite System-Acoustics combination (GNSS-A) technique, which integrates satellite positioning systems and undersea acoustic ranging to determine seafloor crustal deformation at the centimeter level for earthquake disaster prevention. Recently, we found distortion in the SGO-A 10-kHz carrier wave that degraded the accuracy. Carrier wave distortion can cause errors on the scale of several centimeters to twenty centimeters, which greatly impedes centimeter-level observations. This study investigated this carrier wave degradation by an underwater acoustic communication experiment conducted in 2022, using a transducer similar to that used by SGO-A. Also, we reproduced degraded waveforms through a grid search-like method for quantitatively evaluating the extent to which the interior of the equipment contributed to deterioration. Our results underscore the importance of careful consideration in signal processing, as the observed waveform degradation is not solely attributed to hardware structures but also to internal electrical circuits. The findings suggest that conventional signal identification methods may lead to errors, providing motivation for a shift towards experimental and experiential timing-based waveform identification approaches to enhance accuracy in GNSS-A systems.

Temporal Correlation and Message-Passing-Based Sparse Bayesian Learning Channel Estimation for Underwater Acoustic Communications

Temporal Correlation and Message-Passing-Based Sparse Bayesian Learning Channel Estimation for Underwater Acoustic Communications

Measurement of distance and speed between transmitter and receiver using propagation time of underwater acoustic communication signals with orthogonal signal division multiplexing

Abstract This paper proposes a measurement procedure of transmitter-receiver (Tx-Rx) distance using acoustic communication signals to realize communication and positioning underwater using the same signal and device.
Specifically, we focus on an underwater acoustic (UWA) communication using orthogonal signal division multiplexing, where a pilot signal and message are placed in the time-frequency domain during modulation process to measure the delay and Doppler spreads of the UWA channel.
In this paper, we show that both the measurement of distance and speed between the Tx and Rx are available by utilizing the pilot signal.
We conducted a sea trial and evaluated the performance of the proposed method. 
The obtained results suggest that the proposed method can measure the Tx-Rx distance and speed -- an mean absolute error and the standard deviation error of ranging are 4.0 and 2.7~m, respectively, while those of measurement speed are 0.13 and 0.22 m/s, respectively.

Seafloor Sediment Acoustic Properties on the Continental Slope in the Northwestern South China Sea

The acoustic properties of seafloor sediments on continental slopes play a crucial role in underwater acoustic propagation, communication, and detection. To investigate the acoustic characteristics and spatial distribution patterns of sediments on the continental slope, a geoacoustic experiment was conducted in the northwestern South China Sea. The experiment covered two sections: one crossing the shelf and slope in the downslope direction, and the other near the shelf break in the along-slope direction. In situ techniques, sediment sampling, and laboratory measurements were used to acquire data on sediment acoustic properties (such as sound speed and attenuation) and physical properties (including particle composition, density, porosity, and mean grain size). The experimental findings revealed several key points: (1) Acoustic properties of shallow water coarse-grained sediments and deep-sea sediments were higher when measured in the laboratory compared to in situ measurements. (2) Relationships between measured attenuation and physical properties, as well as between sound speed and mean grain size, showed deviations from previous empirical equations. (3) Sediment acoustic and physical properties exhibited significant variations in the downslope direction, while showing gradual variations in the along-slope direction. These variations can be attributed to sedimentary environmental factors such as material sources, hydrodynamic conditions, and water depth.

A joint estimation algorithm for single-input multiple-output underwater acoustic communications

In single-input multiple-output (SIMO) underwater acoustic (UWA) communications, the receiver based on passive time reversal (PTR) combined with decision feedback equalizer (DFE) is widely used but has a limited performance. A multi-channel joint estimation algorithm based on sparse Bayesian learning (MJSBL) is proposed in this paper to exploit the diverse gain from multi-channels, where reasonable prior distribution functions are selected for parameters in the probabilistic model. Afterwards, the algorithm is derived by the mean-field variational inference (VI), iteratively updating the estimation of symbols, channels and noise variation. As a result, the maximum likelihood estimation of the dictionary matrix, as well as the maximum posterior estimation of the channel vectors and noise variance, can be approximated. Simulation and experimental results verify that compared to typical single-channel and multi-channel algorithms, the systems always have lower bit error rates (BERs) and symbol error rates (SERs) with the MJSBL algorithm for different communications distances and symbol block lengths.

Performance of the Direct Sequence Spread Spectrum Underwater Acoustic Communication System with Differential Detection in Strong Multipath Propagation Conditions

The underwater acoustic communication (UAC) operating in very shallow-water should ensure reliable transmission in conditions of strong multipath propagation, significantly disturbing the received signal. One of the techniques to achieve this goal is the direct sequence spread spectrum (DSSS) technique, which consists in binary phase shift keying (BPSK) according to a pseudo-random spreading sequence. This paper describes the DSSS data transmission tests in the simulation and experimental environment, using different types of pseudo-noise sequences: m-sequences and Kasami codes of the order 6 and 8. The transmitted signals are of different bandwidth and the detection at the receiver side was performed using two detection methods: non-differential and differential. The performed experiments allowed to draw important conclusions for the designing of a physical layer of the shallow-water UAC system. Both, m-sequences and Kasami codes allow to achieve a similar bit error rate, which at best was less than 10 −3. At the same time, the 6th order sequences are not long enough to achieve an acceptable BER under strong multipath conditions. In the case of transmission of wideband signals the differential detection algorithm allows to achieve a significantly better BER (less than 10 −2) than nondifferential one (BER not less than 10 −1). In the case of narrowband signals the simulation tests have shown that the non-differential algorithm gives a better BER, but experimental tests under conditions of strong multipath propagation did not confirm it. The differential algorithm allowed to achieve a BER less than 10 −2 in experimental tests, while the second algorithm allowed to obtain, at best, a BER less than 10 −1. In addition, two indicators have been proposed for a rough assessment which of the detection algorithms under current propagation conditions in the channel will allow to obtain a better BER.

An NTRU-Based Certificateless Aggregate Signature Scheme for Underwater Acoustic Communication

An NTRU-Based Certificateless Aggregate Signature Scheme for Underwater Acoustic Communication

Distributed Deep Reinforcement Learning With Prioritized Replay for Power Allocation in Underwater Acoustic Communication Networks

Distributed Deep Reinforcement Learning With Prioritized Replay for Power Allocation in Underwater Acoustic Communication Networks

High-performance deep-sea long-range underwater acoustic communication: Deconvolved conventional beamforming based approach

To address the challenges posed by large propagation loss and severe multipath delay spread, while aiming to improve communication rates in long-range underwater acoustic (UWA) communication, this paper introduces a novel approach: multi-beam (MB) Orthogonal Frequency Division Multiplexing (OFDM) based on deconvolved conventional beamforming (dCv). The proposed method establishes a signal processing framework for UWA channel receivers, wherein received signals corresponding to each angle beam are isolated and concentrated using the dCv technique. Subsequently, the separated signals from each angle undergo maximal-ratio combining (MRC) channel equalization followed by demodulation. Compared to conventional single-beam (SB) processing methods, the proposed approach capitalizes on multipath diversity gain achieved by combining MB outputs originating from various arrival angles. Moreover, employing dCv processing demonstrates superior performance compared to popularly employed beamforming techniques, especially when dealing with paths arriving from closely aligned angles. Additionally, the array beamforming utilized significantly enhances the signal-to-noise ratio (SNR) of each beam output, mitigating the elevated error rates in channel estimation associated with combining low SNR signals received from individual elements. Simulation results utilizing BELLHOP and experimental data from the South China Sea showcase notably improved bit error rate (BER) performance for the proposed method compared to SB equalization, MB-MRC equalization based on conventional beamforming (CBF), minimum variance distortionless response (MVDR), and worst-case performance optimization (WCPO), as well as standard MRC equalization techniques. The proposed receiver achieves error-free decoding results at a communication distance of 80 km with a data rate of 247 bps.

A RNN-based approach to physical layer authentication in underwater acoustic networks with mobile devices

Underwater acoustic communications are becoming a popular solution for underwater data communications and telemetry, making the authentication of transmitted data a necessity. In this paper, we propose a physical-layer authentication strategy for underwater acoustic networks (UWANs) with mobile devices. Such a scenario is more challenging than classical authentication scenarios in static networks, because the mobility of the receiver and/or transmitter implies that channel conditions slowly change over time. Thus, we cannot rely on the statistics of channel features to be stationary. In our proposed strategy, we assume that the receiver can rely on a set of sensors. We first extract a set of channel features, to be used to track the channel evolution over time. We then develop a long short-term memory (LSTM)-based approach, where at each step the sensors predict future feature values based on a learned model and on previously observed feature values. Next, each sensor computes the prediction error and passes it on to the actual receiver, which makes a decision on the signal authenticity through a generalized likelihood ratio test (GLRT). We model different classes of attacks and test them using simulation data obtained via the Bellhop ray tracing software. Numerical results show that our authentication mechanism successfully distinguishes between legitimate and impersonating transmitters, even when considering challenging attacking scenarios where the attacker can successfully mimic the channels between the legitimate transmitter and the sensors.