Underwater Acoustic Channel Model Research Articles

SPACNet: A Simulation Platform of an Acoustic Cognitive Network

Originating from the concept of cognitive networks (CNs), which are becoming popular in wireless terrestrial communication scenarios, underwater acoustic cognitive networks (UACNs) are drawing more and more attention in the field of the Internet of Underwater Things (IoUT). However, as the implementation of cognitive mechanisms in underwater acoustic networks is different from that of wireless scenarios, it is impossible or difficult for traditional simulation platforms to carry out simulations of UACNs. There is a lack of specialized simulation tools in terms of UACNs. To enable the quantitative evaluation of the effectiveness and performance enhancement of a UACNs in an adverse underwater environment, a simulation platform of acoustic cognitive networks (SPACNet) was designed and investigated in this article. First, based on a state machine-based protocol programming framework, the SPACNet is capable of supporting the implementation of different state-transform types associated with cognitive networking protocols. Moreover, to facilitate the realization of cognitive function at comprehensive levels of signal, information, and link, an underwater acoustic channel model with an environmental parameter input is integrated in SPACNet to generate underwater environment-driven multiple-aspect behaviors. Moreover, a simplified collision model consisting of an environment factor, channel response, and node location is used to reduce the complexity of the simulation of UACNs signal reception. A simulation was carried out to verify the effectiveness of SPACNet in evaluating the cognitive capabilities of UACNs. Finally, a field UACNs experiment was performed to validate the general consistency between the conclusion obtained with the SPACNet-based simulation and that from the field test.

A Survey on Physical Layer Techniques and Challenges in Underwater Communication Systems

In the past decades, researchers/scientists have paid attention to the physical layer of underwater communications (UWCs) due to a variety of scientific, military, and civil tasks completed beneath water. This includes numerous activities critical for communication, such as survey and monitoring of oceans, rescue, and response to disasters under the sea. Till the end of the last decade, many review articles addressing the history and survey of UWC have been published which were mostly focused on underwater sensor networks (UWSN), routing protocols, and underwater optical communication (UWOC). This paper provides an overview of underwater acoustic (UWA) physical layer techniques including cyclic prefix orthogonal frequency division multiplexing (CP-OFDM), zero padding orthogonal frequency division multiplexing (ZP-OFDM), time-domain synchronization orthogonal frequency division multiplexing (TDS-OFDM), multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM), generalized frequency division multiplexing (GFDM), unfiltered orthogonal frequency division multiplexing (UF-OFDM), continuous phase modulation orthogonal frequency division multiplexing (CPM-OFDM), filter bank multicarrier (FBMC) modulation, MIMO, spatial modulation technologies (SMTs), and orthogonal frequency division multiplexing index modulation (OFDM-IM). Additionally, this paper provides a comprehensive review of UWA channel modeling problems and challenges, such as transmission loss, propagation delay, signal-to-noise ratio (SNR) and distance, multipath effect, ambient noise effect, delay spread, Doppler effect modeling, Doppler shift estimation. Further, modern technologies of the physical layer of UWC have been discussed. This study also discusses the different modulation technology in terms of spectral efficiency, computational complexity, date rate, bit error rate (BER), and energy efficiency along with their merits and demerits.

Data augmentation method for underwater acoustic target recognition based on underwater acoustic channel modeling and transfer learning

Data augmentation methods as a critical technique in deep learning have not been well studied in the underwater acoustic target recognition, which leads difficult for recognition models to cope with data scarcity and noise interference. This study proposes a data augmentation method based on underwater acoustic channel modeling and Transfer learning to address these challenges. A underwater acoustic channel modeling approach is proposed to generate the augmented signal. A feature-based transfer learning method is presented to narrow the distribution differences between augmented and observed data, and the noise is randomly added to enhance model robustness during training. Dataset acquired in a real-world scenario is used to verify the proposed methods. The proposed methods' effectiveness is proved by utilizing data augmentation in the model training process, which effectively improves the accuracy and noise robustness of the recognition model, especially when observed data is scarce.

Bayesian geoacoustic parameters inversion for multi-layer seabed in shallow sea using underwater acoustic field

Seabed geoacoustic parameters play an important role in underwater acoustic channel modeling. Traditional methods to determine these parameters, for example, drilling, are expensive and are being replaced by acoustic inverse technology. An inversion method based on Bayesian theory is presented to derive the structure and geoacoustic parameters of a layered seabed in a shallow sea. The seabed was considered a layered elastic medium. The objective of this research was to use the sound pressure detected by underwater acoustic sensors at different positions and to use nonlinear Bayesian inversion to estimate the geoacoustic parameters and their uncertainties in the multi-layer seabed. Specifically, the thickness, density, compression wave speed, shear wave speed, and the attenuation of these two wave speeds were determined. The maximum a posterior (MAP) model and posterior probability distribution of each parameter were estimated using the optimized simulated annealing (OSA) and Metropolis-Hastings sampling (MHS) methods. Model selection was carried out using the Bayesian information criterion (BIC) to determine the optimal model that thoroughly explained the experimental data for different parameterizations. The results showed that the OSA is much more capable of delivering high-accuracy results in multi-layer seabed models. The compression wave speed and shear wave speed were less uncertain than the other parameters, and the parameters in the upper layer had less uncertainty than those in the lower layer.

Reinforcement Learning Based Mobile Underwater Localization for Silent UUV in Underwater Acoustic Sensor Networks

Unmanned underwater vehicles (UUVs) that are widely utilized for underwater cooperative combat, underwater environment detection and underwater resource exploration have to be localized by underwater acoustic sensor networks (UASNs). However, the localization accuracy is hard to guarantee due to the limited bandwidths, long propagation latency, and limited energy resources of the UASNs. In this paper, we propose a reinforcement learning (RL) and neural network based mobile underwater localization scheme to optimize the anchor nodes selection in the UASNs to localize the target precisely. More specifically, this scheme applies SqueezeNet to select the line-of-sight (LOS) anchor nodes based on the received signals. In addition, an RL-based approach is further proposed to make further selection from the LOS anchor nodes without knowing the underwater environment model. The Dyna architecture is applied to reduce the convergence time of the anchor nodes selection. Simulation results based on a nonisovelocity geometry-based underwater acoustic channel model show that the proposed schemes significantly improve the localization accuracy and reduce energy consumption of the UASN to achieve trajectory correction.

Statistical Channel Model and Systematic Random Linear Network Coding Based QoS Oriented and Energy Efficient UWSN Routing Protocol

Considering the significance of an energy efficient, delay tolerant and reliable communication protocol for underwater acoustic wireless sensor network (UWSN), this paper proposes a novel systematic random linear network coding (SRLNC) based transmission system examined over a robust statistical UWSN channel model. The derived statistical channel model deals with both the small-scale fading primarily caused by scattering and small wavelength changes and large-scale fading introduced due to node dislocation in the underwater acoustic medium. The proposed SRLNC transmission-based routing approach has been applied over the proposed underwater acoustic (statistical) channel model, and respective performance assessment has been conducted in terms of throughput, energy efficiency, delay and computational complexity by varying network condition parameters. The contributions such as low coefficient vector and Galois filed, low redundant message requirements, computationally efficient pre-coding scheme, iterative buffer flush and enhanced FEC based decoding make the SRLNC based routing protocol sufficiently robust to enable reliable, energy-efficient and delay resilient communication over UWSN. The proposed SRLNC based UWSN routing protocol and its efficacy over dynamic channel conditions affirm that it can be a potential solution for QoS-oriented mission critical underwater communication purposes.

Autoregressive model of an underwater acoustic channel in the frequency domain

The underwater acoustic (UWA) channel model based on the multipath delay–amplitude or the angle of departure (AoD)–angle of arrival (AoA) require many parameters to describe a broadband underwater acoustic (UWA) channel. In this paper, an autoregressive (AR) model is developed to describe the channel in the frequency domain with few parameters. The AR model used here is with an order P, where P is also related to the number of main multipath clusters. Hence, only P + 1 parameters, which consist of the variance of the complex Gaussian white noise (CGWN) and the P pole values of the AR model, are required to describe UWA channel. Each pole value is corresponded to a multipath cluster in the channel, where its phase is correlated with the average multipath delay, and its absolute value is related to the multipath energy. A comprehensive analysis was performed to characterize the statistical distribution of each pole value and the CGWN variance. The results showed that the absolute value and phase of each pole satisfied the Weibull and gamma distributions, respectively, and the variance obeyed a lognormal distribution. Simulation channels were generated with different distributions of the AR model parameters, and the root mean square (RMS) delay obeyed a similar cumulative distribution function as the measured channel.

Linear frequency modulation signal for channel impulse response measurement in shallow water environment

Understanding the characteristics of channel propagation plays a very important role in the design of underwater acoustic communication. Underwater acoustic channel (UAC) model is usually carried out by measuring directly at a specific location and time. This paper presents the use of Linear Frequency Modulation (LFM) signal for channel impulse response estimation and power delay profile (PDP) measurement in a shallow water environment. Measurements were made in a laboratory-scale towing tank with three variations of distance and depth. Furthermore, the measurement results are compared with the existing underwater acoustic channel model. The measurement results show that the response impulses at the three distances have almost the same pattern and the resulting amplitude is similar to the existing underwater acoustic channel model simulation. The RMS delay spread generated from the three distances has a value of about 0,2 msec. Meanwhile, the maximum excess delay obtained at a distance of 120 m has the highest value, which is 29 msec.

Design of Algorithms and Protocols for Underwater Acoustic Wireless Sensor Networks

Nowadays, with the recent advances of wireless underwater communication and acoustic sensor devices technology, we are witnessing a surge in the exploration and exploitation of the ocean’s abundant natural resources. Accordingly, to fulfill the requirements of the exploration of the ocean, researchers have focused their work toward the design of methods and algorithms for the underwater acoustic sensor networks (UASNs). Although considerable research effort has been devoted to the development of a variety of UASN-based applications, very limited work has addressed the algorithmic design and analysis for UASN. To this end, we propose to provide a comprehensive design, development, and analysis of algorithms and protocols for UASNs. We discuss each of the fundamental UASN building blocks, such as (i) underwater acoustic communication channel modeling, (ii) sustainable coverage and target detection, (iii) Medium Access Control (MAC-layer design and time synchronization, (iv) localization algorithms design, and (v) underwater routing protocol. Then, we illustrate the different protocols from each category and compare their benefits and drawbacks. Finally, we discuss a few potential directions for future research related to the design of future generations of UASNs.

Capacity of Uplink Partial Overlapping Non-Orthogonal Multiple Access for Underwater Acoustic Networks

The unique characteristic of bandwidth-distance relationship in underwater acoustic (UWA) channels makes standard uplink non-orthogonal multiple access (NOMA) scheme not be applicable in general underwater acoustic networks (UWANs). In this article, we propose an uplink partial overlapping non-orthogonal multiple access (PONOMA) scheme for UWANs, and investigate capacity region of uplink PONOMA in UWANs. By formulating the problem of the optimal energy distribution for uplink PONOMA based on UWA channel modeling, the closed-form solutions for optimal power spectral density (p.s.d.) and capacity region are derived. Furthermore, we modify the channel modeling by building in parameter uncertainty induced by the empirical nature of UWA channel modeling using box sets, and derived robust capacity region under parameter uncertainty. Numerical results are provided to demonstrate the performance of our proposed scheme.

Research on acoustic conduction mechanism of underwater acoustic channel based on metamaterials

In underwater acoustic communication, there are problems of low transmission efficiency, severe loss, and inaccurate point-to-point transmission. To realize the efficient transmission of underwater acoustic communication based on finite element analysis, a metamaterial-based underwater acoustic channel model was designed using COMSOL Multiphysics 5.3 software, and its acoustic conduction mechanism was studied. It was found that the directional transmission of sound waves with low loss was achieved when the sound waves generated by the point sound source pass through the underwater acoustic channel. In addition, the periodic structure of local resonance was proposed to generate the multi-directional acoustic waves, which can control the acoustic wave transmission direction arbitrarily and improve the transmission efficiency of underwater acoustic communication. This indicates a new direction for long-distance and efficient transmission of underwater acoustic communication.

Development of Underwater Acoustic Channel Model for Wireless Sensor Network in Tank

The physical quantity of interest can be detected using wireless sensor network. The concept of wireless sensor network used to explore difficult areas to access is extended to underwater applications. Efforts are made to focus on design and development of reliable, feasible and robust system for communication in underwater environment. The scenario of communication is completely different for terrestrial and underwater environment. Underwater wireless communication is accomplished by transmission of acoustic signal. Requirement exists to develop a model governing basic equations for acoustic frequency range for underwater acoustic communication. With excess quantity of sodium chloride in a underwater tank, the physical properties of the channel changes which alternately effects the communication. Using soft computing technique, the attenuation model is simulated which is a basic physical property taking change during underwater acoustic communication. The topology of sensor network in water is another challenging task because behaviors of acoustic sensor in underwater are completely different than terrestrial sensors. Thus the efforts are made to devise a model of acoustic frequency environment in water using basic relationships of various physical phenomena. The Channel propagation model is devised that helps to understand percentage area coverage for the received signal strength of the transmitted acoustic signal. Thus the underwater acoustic signal channel propagation model is presented which helps to focus on communication scenario in water and proceed for application.

Analytical method of parameter determination for OFDM system over measurement-based underwater acoustic channel modeling

In underwater acoustic (UWA)-OFDM systems, the major problem in implementation of complex equalization algorithms at receiver can be avoided by finding appropriate system parameters. This paper proposes an analytical method for determining the UWA-OFDM system parameters in order to maximize the achievable system capacity and to limit interference power. Unlike most existing research studies that analyzed the system performance without consideration of the inter-carrier interference (ICI), we focus on evaluating the UWA-OFDM system performance under both the ambient noise and ICI effect. The signal-to-interference-plus-noise ratio and the achievable system capacity are formulated by using the simulation UWA channel model, which is derived from the measurement data of the real UWA channel from a very shallow water environment in West Lake, Hanoi, Vietnam. Using the proposed method, the UWA-OFDM system parameters including the symbol duration, the number of subcarriers, the system bandwidth, and the transmit power are determined to achieve the maximal spectral efficiency of 3.2bits/sec/Hz. The proposed analytical method can be used as a practical guideline to determine appropriate transmission parameters for the design of UWA-OFDM systems.

Channel Modeling for Underwater Acoustic Network Simulation

Simulation forms an important part of the development and empirical evaluation of underwater acoustic network (UAN) protocols. The key feature of a credible network simulation model is a realistic channel model. A common approach to simulating realistic underwater acoustic (UWA) channels is by using specialised beam tracing software such as BELLHOP. However, BELLHOP and similar modeling software typically require knowledge of ocean acoustics and a substantial programming effort from UAN protocol designers to integrate it into their research. This paper is a distilled tutorial on UWA channel modeling with a focus on network simulation, providing a trade-off between the flexibility of low level channel modeling via beam tracing and the convenience of automated channel modeling, e.g. via the World Ocean Simulation System (WOSS). The tutorial is accompanied by our MATLAB simulation code that interfaces with BELLHOP to produce channel data for UAN simulations. As part of the tutorial, we describe two methods of incorporating such channel data into network simulations, including a case study for each of them: 1) directly importing the data as a look-up table, 2) using the data to create a statistical channel model. The primary aim of this paper is to provide a useful learning resource and modeling tool for UAN protocol researchers. Initial insights into the UAN protocol design and performance provided by the statistical channel modeling approach presented in this paper demonstrate its potential as a powerful modeling tool for future UAN research.

Design of Underwater Acoustic Channel Model for OFDM Communication System

The paper describes the design of underwater acoustic channel model for OFDM communication system. The underwater acoustic channel considered includes multipath effect, attenuation loss, absorption loss, spreading loss and total noise due to thermal Noise, turbulence Noise, shipping Noise, wave Noise. The acoustic channel model used for OFDM Communication will have the noise effect due to attenuation loss and ambient noise (Total Noise). In this research work, In the underwater channel, Multipath parameters such as length, width and depth and attenuation parameters such as frequency, salinity, radial range, SPS and ambient noise parameters such as shipping factor, wave factor are considered in calculating total noise.

Cross-Layer Network Lifetime Maximization in Underwater Wireless Sensor Networks

A cross-layer design methodology that jointly optimizes the link-layer network flow rate and the physical layer transmission power wherein rate is developed for energy-constrained underwater wireless sensor networks. The objective of the design is to maximize the lifetime of the network operation for a given network topology and a bound of the total transmission time of all links. Initially, each node is set to transmit at the most energy-efficient transmission rate, which is derived using an underwater acoustic channel model. A constrained least square problem then is formulated which yields an analytical solution of the optimal network flow at each link that maximizes the network lifetime. If the timing constraint is not met, a new iteration will begin with the restriction on per-node energy consumption incrementally relaxed. Usually, the algorithm converges within a couple of iterations. Two design examples, a linear configured network, and a rhombus configured network are used to demonstrate the design procedures. Extensive simulations have been performed and superior performance (longer network lifetime) of this proposed design has been observed.

Rational-Orthogonal-Wavelet-Based Active Sonar Pulse and Detector Design

A family of rational orthogonal wavelets is explored in active sonar detection to achieve Doppler robustness and noise mitigation. The broadband active sonar system is classified as wavelet-based noncoherent subband energy detection. It features a flexible broadband sonar pulse design with low peak-to-average power ratio (PAPR), and a detector of low computation complexity via fast rational wavelet filter bank. The designed family of broadband pulses is based on a combination of multiple basis functions of the complex rational orthogonal wavelet (CROW). Differing from the conventional dyadic wavelet (with an integer scale factor of 2), the CROW has a rational scale factor and much higher resolution in the partition of the time-scale plane. This family of wavelets presents great flexibility in the system design. Design example is presented with minimized PAPR to serve for applications demanding the stealth. The sonar detector is based on the CROW analysis filter bank. Detection performance is analyzed regarding its resistance to Doppler noise and multipath by simulations using a geometric underwater acoustic channel model. The performance of the wavelet-based active sonar system is compared with a linear frequency modulated pulse-based system. The receiver operating characteristic curves demonstrate that the designed system is able to cope with severe multipath, high ambient noise, and severe Doppler dispersion. The framework provides possible solutions for underwater applications in low signal-to-noise ratio and varying mobility conditions.

An Energy-Efficient and Obstacle-Avoiding Routing Protocol for Underwater Acoustic Sensor Networks.

Underwater Acoustic Sensor Networks (UASNs) have become one of the promising technologies for exploring underwater natural resources and collecting scientific data from the aquatic environment. As obstacles hinder the communications among sensor nodes in UASNs, designing an effective bypass routing protocol to avoid obstacles is an urgent need. Moreover, the sensor nodes are typically powered by batteries, which are difficult to replace, restricting the network lifetime of UASNs. In this paper, an Energy-efficient and Obstacle-Avoiding Routing protocol (EOAR) is proposed not only to address the issue of marine animals acting as obstacles that interfere with communications, but also to balance the network energy according to the residual energy. In the EOAR protocol, when the current node perceives the existence of marine animals, the interference area of the animal-nodes is first calculated using the underwater acoustic channel model, and then the candidate forwarding relay set of the current node is obtained according to the constraint conditions. The optimal candidate forwarding relay is determined by a fuzzy logic-based forwarding relay selection scheme based on considering the three parameters of the candidate forwarding relay, which includes the propagation delay, the included angle between two neighbor nodes, and the residual energy. Furthermore, in order to solve the problem of energy waste caused by packet collision, we use a priority-based forwarding method to schedule the packet transmission from the candidate forwarding relay to the destination node. The proposed EOAR protocol is simulated on the Aqua-sim platform and the simulation results show that proposed protocol can increase the packet delivery ratio by 28.4% and 11.8% and can reduce the energy consumption by 53.4% and 32.7% and, respectively, comparing with the hop-by-hop vector-based forwarding routing protocol (HHVBF) and void handling using geo-opportunistic routing protocol (VHGOR).

A Nonisovelocity Geometry-Based Underwater Acoustic Channel Model

This paper proposes a new geometry-based shallow underwater acoustic (UWA) channel model allowing for nonisovelocity ocean conditions. The fact that the isovelocity assumption does not hold in many real-world scenarios motivates the need for developing channel models for nonisovelocity UWA propagation environments. Starting from a geometrical model, we develop a stochastic channel model for a single-input single-output (SISO) vehicle-to-vehicle UWA channel assuming that the ocean surface and bottom are rough and that the speed of sound varies with depth. The effect of the nonisovelocity condition has been assessed regarding its influence on the temporal autocorrelation function, the frequency correlation function (FCF), and the power delay profile of the UWA channel model. The UWA channel model has also been validated by matching its FCF as well as the therefrom derived main characteristic quantities, such as the average delay, delay spread, and coherence bandwidth against measurement data. The proposed UWA channel model is very useful for the design and performance analysis of UWA communication systems under realistic propagation conditions.

Optimal Redundancy Control Strategy for Fountain Code-Based Underwater Acoustic Communication

In this paper, a transmission redundancy optimization strategy for fountain codes that uses an adaptive filtering technique as well as recent results concerning the upper bound of the source packet erasure probability for fountain codes over finite fields is proposed. The performance of the proposed strategy was evaluated in static and simulated realistic underwater acoustic channel environments simulated by a recently proposed statistical underwater acoustic channel model. The goal of this investigation is to improve the communication efficiency of underwater acoustic sensor networks that use communication protocols based on fountain codes. The performance of the proposed strategy is compared with the recently proposed approaches of discrete stochastic approximation (DSA) and the joint power and rate control (JPR) schemes. The simulation results demonstrate that the strategy proposed in this paper performs better than the existing schemes in both static and simulated realistic environments. The proposed strategy is 4.75 times better than the DSA in the static convergence performance evaluation. Further analysis shows that in the presence of a simulated realistic environment, compared to DSA and JPR, the strategy proposed in this paper reduces the overall transmission redundancy by approximately 11.4% and 52.6%, respectively. It also improves the average communication efficiency by 1.3% and 12.5%, respectively. The average optimization error relative to optimal redundancy is improved by approximately 62.1% and 92.5%, respectively. These numerical results are obtained by employing the specific simulation parameters and the simulated environment mentioned in this paper.