Abstract : Influenced by environmental conditions, underwater acoustic (UWA) communication channels exhibit spatial and temporal variations, posing significant challenges for UWA networking and applications. This dissertation develops statistical signal processing approaches to model and predict variations of the channel and relevant environmental factors. Firstly, extensive field experiments are conducted in the Great Lakes region. Three types of the freshwater river/lake acoustic channels are characterized in the aspects of statistical channel variations and sound propagation loss, including stationary, mobile and under-ice acoustic channels. Statistical data analysis shows that relative to oceanic channels, freshwater river/lake channels have larger temporal coherence, higher correlation among densely distributed channel paths, and less sound absorption loss. Moreover, variations of the under-ice channels are less severe than those in open water in terms of multipath structure and Doppler effect. Based on the observed channel characteristics, insights on acoustic transceiver design are provided, and the following two works are developed. online modeling and prediction of slowly-varying channel parameters are investigated, by exploiting their inherent temporal correlation and correlation with water environment. The temporal evolution of the channel statistics is modeled as the summation of a time-varying environmental process, and a Markov latent process representing unknown or unmeasurable physical mechanisms. An algorithm is developed to recursively estimate the unknown model parameters and predict the channel parameter of interest. The above model and the recursive algorithm are further extended to the channel that exhibits periodic dynamics. The proposed models and algorithms are evaluated via extensive simulations and data sets from two shallow-water experiments. The experimental results reveal that the average channel-gain-to-noise-power ratio, the fast fading statistics, and the average delay spread can be well predicted. The inhomogeneity of the sound speed distribution is challenging for Autonomous underwater vehicles (AUVs) communications and acoustic signaling-based AUV localization due to the refraction effect. Based on the time-of-flight (TOF) measurements among the AUVs, a distributed and cooperative algorithm is developed for joint sound speed estimation and AUV tracking. The joint probability distribution of the time-of-flight (TOF) measurements, the sound speed parameters and the AUV locations are represented by a factor graph, based on which a Gaussian message passing algorithm is proposed after the linearization of nonlinear measurement models. Simulation results show that the AUV locations and the sound speed parameters can be tracked with satisfying accuracy. Moreover, significant localization improvement can be achieved when the sound speed stratification effect is taken into consideration.
Digital Underwater Acoustic Communications focuses on describing the differences between underwater acoustic communication channels and radio channels, discusses loss of transmitted sound in underwater acoustic channels, describes digital underwater acoustic communication signal processing, and provides a comprehensive reference to digital underwater acoustic communication equipment. This book is designed to serve as a reference for postgraduate students and practicing engineers involved in the design and analysis of underwater acoustic communications systems as well as for engineers involved in underwater acoustic engineering. Introduces the basics of underwater acoustics, along with the advanced functionalities needed to achieve reliable communications in underwater environment Identifies challenges in underwater acoustic channels relative to radio channels, underwater acoustic propagation, and solutions Shows how multi-path structures can be thought of as time diversity signals Presents a new, robust signal processing system, and an advanced FH-SS system for multimedia underwater acoustic communications with moderate communication ranges (above 20km) and rates (above 600bps) Describes the APNFM system for underwater acoustic communication equipment (including both civil and military applications), to be employed in active sonar to improve its performance
Abstract : The underwater acoustic network testbed helps to validate the theoretical results and bridge the gap between experimental results. Characterizing and modeling the spatial-temporal dynamics of underwater acoustic channels is essential to developing efficient and effective physical-layer communication algorithms and network protocols. This work dedicates to designing a testbed system to measure the spatial-temporal dynamics of underwater acoustic channels. The collected measurements will shed insights into the spatial-temporal correlation of underwater acoustic channels and will be used to evaluate the theoretical algorithms that are designed to model the spatial-temporal dynamics and to exploit the spatial-temporal dynamics for more efficient and effective underwater system operations. The report speaks about how to tackle the above problem and discusses the following aspects in detail which are, individual node design which is controlled by a raspberry pi, comparison of the current test bed with the existing testbeds in field, complete description of the server algorithm and its error handling techniques, development of the server level GUI and web-based GUI and finally some of the experimentations carried out in Portage lake and Keweenaw bay.
The ocean covers more than 70% of the earth, which provides rich biological, chemical, mineral and space resources for the development of human civilization. The cause of managing the ocean is of strategic importance to our economic development and national security. Acoustic wave is the most widely used and mature underwater information transmission carrier known to mankind. Underwater acoustic (UWA) communication technology is one of the main technical supports to carry out various marine activities, but it is challenged by the complex marine environment, specifically in terms of propagation loss, UWA environmental noise, multipath propagation characteristics, Doppler expansion, spatial and temporal variation effects and other scientific issues, which restricts the improvements of the bit error rate (BER) performance, communication rate, communication distance, robustness and other indicators. The current level of development of UWA communication technology is difficult to fully meet the needs of practical applications.Channel estimation is an effective technical means to solve the problems of multipath effect and temporal- spatial variation characteristics. Recent breakthroughs in adaptive methods and machine learning in various fields have brought new opportunities for the further development of UWA channel estimation technology, but also raised new technical problems, such as the use of channel structure characteristics, sample scarcity training, label missing training, domain mismatch caused by environmental changes. These problems make the effectiveness and applicability of the new method seriously restricted, and it is difficult to bring out the proper information sensing ability.Based on the frontier of intelligent ocean and marine information science, this thesis focuses on the scientific problems of UWA communication in complex marine environment according to the development needs of national marine strategy, aims at the key technical problems faced by adaptive and machine learning channel estimation methods, such as analysis of channel cluster sparsity characteristics, limited data, label missing, domain mismatch, etc., and introduces optimization methods, neural network model design and analysis, data augmentation methods, transfer learning and other recent academic results. We have explored the mechanism of adaptive and machine learning based channel estimation methods and finally proposed a series of new methods for channel estimation based on adaptive signal processing and machine learning.
A modulation technique for increasing the reliable data rate achievable by an underwater acoustic communication system is presented and demonstrated. The technique, termed spatial modulation, seeks to control the spatial distribution of signal energy such that multiple parallel communication channels are supported by the single, physical ocean channel. Results from several experiments successfully demonstrate higher obtainable data rates and power throughput. Given a signal energy constraint, a communication architecture with access to parallel channels will have increased capacity and reliability as compared to one with access to a single channel. Assuming the use of multiple element spatial arrays at both the transmitter and receiver, an analytic framework is developed that allows a multiple input, multiple output physical channel to be transformed into a set of virtual parallel channels. The continuous time, vector singular value decomposition is the primary vehicle for this transformation. Given knowledge of the channel impulse responses and assuming additive, white Gaussian noise as the only interference, the advantages of using spatial modulation over a deterministic channel may be exactly computed. Improving performance over an ensemble of channels using spatial modulation is approached by defining and then optimizing various average performance metrics including average signal to noise ratio, average signal to noise plus interference ratio, and minimum square error. Several field experiments were conducted. Detailed channel impulse response measurements were made enabling application of the decomposition methodology. The number, strength, and stability of the available parallel channels were analyzed. The parallel channels were readily interpreted in terms of the underlying sound propagation field. Acoustic communication tests were conducted comparing conventional coherent modulation to spatial modulation. In one case, a reliable data rate of 24000 bits per second with a 4 kHz bandwidth signal was achieved with spatial modulation when conventional signaling could not achieve that rate. In another test, the benefits of spatial modulation for a horizontally distributed communication system, such as an underwater network with autonomous underwater vehicles, were validated.
Estuaries are water regions that connect rivers and oceans, which are very important due to heavy traffic, fishery and other coastal engineering activities. Underwater acoustic technology offers a series of effective applications and technical supports for real-time monitoring and long-term preservation of the nature environment and ecosystem in these regions. However, estuaries are shallow waters with complicated temporal and spatial environmental variability, involving a variety of physical oceanographic processes, such as tidal water mixing and ocean winds/waves, which can significantly influence the underwater sound propagation and moreover, underwater acoustic communications. In order to perform reliably and effectively in such complex time-varying shallow-water ocean environments, next-generation underwater acoustic communication systems need an all new design based on the environmental variability of the physical ocean, which takes the environmental physics and time-varying variability into account and is able to adapt and switch to the optimal mode as the environment evolves. Therefore, a deep, comprehensive and thorough understanding of the link between the time-varying ocean environment, underwater acoustic channel, and underwater acoustic communication systems is highly required. ☐ This dissertation investigated the relationship between the shallow-water, time-varying environment of estuaries, the underwater sound propagation and underwater acoustic communications, which can help the design of underwater acoustic systems so that they can adapt the time-varying environment with wiser parameter configurations. In this dissertation, field data analysis, joint numerical modeling, together with a controllable laboratory experiment were used to study acoustic channel variability of a shallow estuary and its influence on the performance of underwater acoustic communications. This dissertation included four aspects: (a) Effect of water-column variation due to the tidal dynamics in an estuary on the underwater acoustic direct path; (b) Effect of time-varying surface roughness due to the wind-driven waves on underwater acoustic surface paths; (c) Numerically modeling the effect of time-varying wind-driven shallow-water waves on coherent underwater acoustic communications using a combined model; (d) Conducting a controllable laboratory experiment to investigate the time-varying wind-driven water waves on the performance of coherent and non-coherent underwater acoustic communications. ☐ The first two aspects focused on the link between the time-varying environment of an estuary and the underwater acoustic wave propagation. With field data analysis and joint numerical modeling, the time-varying variability of acoustic direct paths and surface-bounced paths from a high-frequency acoustic experiment conducted in the Delaware Bay estuary was explored. On one hand, periodical acoustic direct path fading was found in the tidal-straining Delaware Bay estuary, with the fading period as same as the semi-diurnal tide. Based on physical oceanography and ocean acoustics, the mechanism that causes the direct path fading and its link to the water dynamics of an estuary was investigated. On the other hand, the relationship between the acoustic surface paths and the surface wind speed was investigated, and the wind-influenced shallow-water time-varying channel was studied using field data analysis and a joint model combining physical oceanography and ocean acoustics. The joint numerical model, including a wind-wave model, a surface generation algorithm and a parabolic equation acoustic model, reproduced the relationship between the wind speed and surface reflection signals. ☐ The last two aspects applied the knowledge of underwater sound propagation in shallow estuaries into analyzing the performance of underwater acoustic communication systems, i.e., investigating how the fast fluctuation of a shallow-water environment (wind-driven waves) influences different fundamental modulation schemes for underwater acoustic communications. To better analyze the effect of environmental variability of the physical ocean on underwater acoustic communications, the surface condition was set as the only variation in the numerical modeling and the controllable laboratory experiment. On one hand, a combined model including physical oceanography, ocean acoustics, and underwater acoustic communication was used to study the time-varying underwater acoustic channel under different wind speeds, and the performance of the coherent acoustic communication (QPSK) system. On the other hand, a controllable laboratory experiment was conducted to investigate bit-error-rate (BER) performance of the MFSK (representing the non-coherent acoustic communication) and the QPSK (representing the coherent acoustic communication) acoustic modulations. ☐ The main conclusions of the dissertation are as follows. For the time-varying variability of underwater acoustic channel: (a) Due to the tidal-straining water dynamics of an estuary, periodical water column exchange between the seawater and the freshwater, up-refracting sound speed profile is more likely to form by the end of ebb tide, which redirects sound signal away from the deep receivers and creates shadow zone for the sound direct path; (b) In an open estuary, the acoustic pressure of surface-bounced paths decreases with increased wind speed, as a result of increased acoustic scattering due to the wind-driven surface roughness. For underwater acoustic communications: (c) Coherent acoustic communications are sensitive to the fast time-varying variability, and performance decrease significantly with increased wind speed, as a result of increased channel variability and decreased temporal coherence; (d) Non-coherent acoustic communications are less sensitive to the channel variability, and the reduced multipath signals due to wind-wave surface may improve the system performance. ☐ The key novelties of this dissertation include: (a) Using a joint model involving physical oceanography and ocean acoustics to study the effect of time-varying estuarine environment (water-column variations and wind-driven surface waves) on underwater sound propagation and the underwater acoustic channels. (b) Using an integrated model involving physical oceanography, ocean acoustics, and underwater acoustic communications to study the effect of time-varying estuarine environment (wind-driven surface waves) on underwater acoustic communications. (c) Using field experimental data, numerical modeling and controllable laboratory experiment to study the underwater sound propagation and underwater acoustic communications in a time-varying ocean environment.
Abstract : Underwater acoustic (UWA) communication networks are promising techniques for medium- to long-range wireless information transfer in aquatic applications. The harsh and dynamic water environment poses grand challenges to the design of UWA networks. This dissertation leverages the advances in machine learning and signal processing to develop intelligent and secure UWA communication networks. Three research topics are studied: 1) reinforcement learning (RL)-based adaptive transmission in UWA channels; 2) reinforcement learning-based adaptive trajectory planning for autonomous underwater vehicles (AUVs) in under-ice environments; 3) signal alignment to secure underwater coordinated multipoint (CoMP) transmissions. First, a RL-based algorithm is developed for adaptive transmission in long-term operating UWA point-to-point communication systems. The UWA channel dynamics are learned and exploited to trade off energy consumption with information delivery latency. The adaptive transmission problem is formulated as a partially observable Markov decision process (POMDP) which is solved by a Monte Carlo sampling-based approach, and an expectation-maximization-type of algorithm is developed to recursively estimate the channel model parameters. The experimental data processing reveals that the proposed algorithm achieves a good balance between energy efficiency and information delivery latency. Secondly, an online learning-based algorithm is developed for adaptive trajectory planning of multiple AUVs in under-ice environments to reconstruct a water parameter field of interest. The field knowledge is learned online to guide the trajectories of AUVs for collection of informative water parameter samples in the near future. The trajectory planning problem is formulated as a Markov decision process (MDP) which is solved by an actor-critic algorithm, where the field knowledge is estimated online using the Gaussian process regression. The simulation results show that the proposed algorithm achieves the performance close to a benchmark method that assumes perfect field knowledge. Thirdly, the dissertation presents a signal alignment method to secure underwater CoMP transmissions of geographically distributed antenna elements (DAEs) against eavesdropping. Exploiting the low sound speed in water and the spatial diversity of DAEs, the signal alignment method is developed such that useful signals will collide at the eavesdropper while stay collision-free at the legitimate user. The signal alignment mechanism is formulated as a mixed integer and nonlinear optimization problem which is solved through a combination of the simulated annealing method and the linear programming. Taking the orthogonal frequency-division multiplexing (OFDM) as the modulation technique, simulation and emulated experimental results demonstrate that the proposed method significantly degrades the eavesdropper's interception capability.
"Several statistical properties of underwater acoustic channels gathered from experiment data are analyzed. The baseband channel impulse response (CIR) is estimated using a time domain least squares technique with a sliding window applied to the probing sequences. From the CIR estimation, the probability distribution functions (PDFs) of the magnitude, real part, imaginary part, and phase of the CIR are calculated. Gamma, Rayleigh, and compound k distributions are fitted to the magnitude PDF and the fitness of the distributions are calculated with a two-sample Kolmogorov-Smirnov test. Other statistics such as the autocorrelation function, coherence time, and scattering function are evaluated. The results show that the underwater acoustics channels are worse than the Rayleigh fading commonly seen as the worst case radio channel. Furthermore, the spatial and intertap correlation matrices of multiple input multiple output (MIMO) systems are estimated using experimental data. It is shown that underwater acoustic MIMO channels exhibit high spatial and temporal correlation. The bit error rate (BER) of the receiver using Frequency-domain turbo equalization is also evaluated in different channel correlation setups, demonstrating strong effects of the spatial-temporal correlation function on the performance"--Abstract, leaf iv.
High data rate acoustic communications become feasible with the use of communication systems that operate at high frequency. The high frequency acoustic transmission in shallow water endures severe distortion as a result of the extensive intersymbol interference and Doppler shift, caused by the time variable multipath nature of the channel. In this research a Single Input Multiple Output (SIMO) acoustic communication system is developed to improve the reliability of the high data rate communications at short range in the shallow water acoustic channel. The proposed SIMO communication system operates at very high frequency and combines spatial diversity and decision feedback equalizer in a multilevel adaptive configuration. The first configuration performs selective combining on the equalized signals from multiple receivers and generates quality feedback parameter for the next level of combining. The second configuration implements a form of turbo equalization to evaluate the individual receivers using the feedback parameters as decision symbols. The improved signals from individual receivers are used in the next iteration of selective combining. Multiple iterations are used to achieve optimal estimate of the received signal. The multilevel adaptive configuration is evaluated on experimental and simulated data using SIMO system with three, four and five receivers. The simulation channel model developed for this research is based on experimental channel and Rician fading channel model. The performance of the channel is evaluated in terms of Bit Error Rate (BER) and Signal-to-Noise-and-Interference Ratio (SNIR). Using experimental data with non-zero BER, multilevel adaptive spatial diversity can achieve BER of 0 % and SNIR gain of 3 dB. The simulation results show that the average BER and SNIR after multilevel combining improve dramatically compared to the single receiver, even in case of extremely high BER of individual received signals. The results demonstrate the ability of the proposed multilevel adaptive combining approach to significantly improve the performance of the shallow water acoustic channel, while preserving the same transmission power and channel bandwidth.
Acoustic channel models provide a tool for predicting the performance of underwater communication systems prior to deployment, and are thus essential for system design. In this dissertation, we offer a statistical channel model, which incorporates physical laws of acoustic propagation (frequency-dependent attenuation, bottom-surface reflections) as well as the effects of inevitable random local displacements. We focus on random displacements on two scales: small-scale effects, that involve distances on the order of a few wavelengths, and large-scale effects, that involve many wavelengths. Small-scale effects include scattering and motion-induced Doppler shifting, and are responsible for fast variations of the instantaneous channel response; while large-scale effects describe the location uncertainty and changing environmental conditions, and affect the locally-averaged received power. We model each propagation path by a large-scale gain and micro-multipath components that cumulatively result in a complex Gaussian distortion. Random surface motion and transducer displacement introduce additional variation whose temporal correlation is described by Bessel-type functions. The total power, or the gain contained in the channel, averaged over small-scale, is modeled as log-normally distributed. The models are validated using real data obtained from four experiments. Specifically, experimental data are used to assess the distribution and the auto-correlation functions of the large-scale transmission loss and the short-term path gains. While the former indicates a log-normal distribution with an exponentially decaying auto-correlation, the latter indicates a conditional Ricean distribution with Bessel-type auto-correlation. Based on the proposed model, we design a channel simulator which we employ to generate a time-varying channel whose statistical characteristics match with those of a real underwater channel. The simulated channel is applied to convey an OFDM signal to coherent and differentially coherent detectors, and the MSE performance of the experimental and simulated systems are shown to be similar. Finally, we investigate the feasibility of adaptive power control using an experimental data set as well as theoretically. Based on the observed time-correlation properties of the large-scale channel gain, linear power prediction is employed and achievable power savings are obtained analytically (assuming a log-normal gain distribution) and experimentally. The results indicate that substantial power savings are possible over extended periods of time.
