Download or read book Adapting Deep Learning for Underwater Acoustic Communication Channel Modeling written by and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract : The recent emerging applications of novel underwater systems lead to increasing demand for underwater acoustic (UWA) communication and networking techniques. However, due to the challenging UWA channel characteristics, conventional wireless techniques are rarely applicable to UWA communication and networking. The cognitive and software-defined communication and networking are considered promising architecture of a novel UWA system design. As an essential component of a cognitive communication system, the modeling and prediction of the UWA channel impulse response (CIR) with deep generative models are studied in this work. Firstly, an underwater acoustic communication and networking testbed is developed for conducting various simulations and field experiments. The proposed test-bed also demonstrated the capabilities of developing and testing SDN protocols for a UWA network in both simulation and field experiments. Secondly, due to the lack of appropriate UWA CIR data sets for deep learning, a series of field UWA channel experiments have been conducted across a shallow freshwater river. Abundant UWA CIR data under various weather conditions have been collected and studied. The environmental factors that significantly affect the UWA channel state, including the solar radiation rate, the air temperature, the ice cover, the precipitation rate, etc., are analyzed in the case studies. The obtained UWA CIR data set with significant correlations to weather conditions can benefit future deep-learning research on UWA channels. Thirdly, a Wasserstein conditional generative adversarial network (WCGAN) is proposed to model the observed UWA CIR distribution. A power-weighted Jensen-Shannon divergence (JSD) is proposed to measure the similarity between the generated distribution and the experimental observations. The CIR samples generated by the WCGAN model show a lower power-weighted JSD than conventional estimated stochastic distributions. Finally, a modified conditional generative adversarial network (CGAN) model is proposed for predicting the UWA CIR distribution in the 15-minute range near future. This prediction model takes a sequence of historical and forecast weather information with a recent CIR observation as the conditional input. The generated CIR sample predictions also show a lower power-weighted JSD than conventional estimated stochastic distributions.

Download or read book The Research on Adaptive and Machine Learning Methods in Underwater Acoustic Channel Estimation written by Yonglin Zhang and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Machine Learning Modeling for IoUT Networks written by Ahmad A. Aziz El-Banna and published by Springer Nature. This book was released on 2021-05-29 with total page 71 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses how machine learning and the Internet of Things (IoT) are playing a part in smart control of underwater environments, known as Internet of Underwater Things (IoUT). The authors first present seawater’s key physical variables and go on to discuss opportunistic transmission, localization and positioning, machine learning modeling for underwater communication, and ongoing challenges in the field. In addition, the authors present applications of machine learning techniques for opportunistic communication and underwater localization. They also discuss the current challenges of machine learning modeling of underwater communication from two communication engineering and data science perspectives.

Download or read book Intelligent and Secure Underwater Acoustic Communication Networks written by and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Adaptive Feature Representation to Improve Interpret and Accelerate Channel Estimation and Prediction for Shallow Water Acoustic Environments written by Ryan A. McCarthy (PhD) and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In my doctoral dissertation I investigate new approaches to real-time channel estimation of underwater acoustic communications that complement existing estimation techniques. Modified sparse optimization algorithms have been used to improve channel estimation with some success. This work aims to improve these algorithms by applying pattern recognition through adaptive signal processing and machine learning to accelerate estimation time. Specifically, it investigates a model-agnostic geometric feature morphology based on braid theory to interpret diverse channel phenomena. The computational goal is to detect, separate and interpret multipath features in the channel delay spread across time, frequency, and varying degrees of channel sparsity. The main contribution of the thesis is development of braids feature representations and related channel tracking and learning algorithms to track salient bands of multipath activity. We develop robust signal processing and braided feature engineering approaches that evolve dynamically to the fluctuating channel multipath activity. To test the hypothesis that braids can track and adapt to diverse activity developing within the channel, simulated shallow water environments created through the well-known BELLHOP model and data from the SPACE08 field experiment are examined. Several simulated shallow water environments are examined with additive white Gaussian noise and varying degrees of activity to evaluate the performance of braiding and machine learning for shallow water acoustic channel estimation and interpretation. Performance is evaluated through visual confirmation and ground truths are provided by BELLHOP's outputs (e.g. eigenrays, arrivals, etc.). Results show that braids can evolve to capture dynamically changing multipath scattering activity in the shallow water acoustic channel. Furthermore, we demonstrate that leveraging braid feature representations with acoustic physics propagation models can successfully predict the number of reflectors in active channel multipath. We also demonstrate the significance of braid manifold representation in improving the computational speed for channel estimation. On average, this technique has improved estimation speed by ~.02 seconds as compared to the existing estimation techniques. These results suggest that braids can be used for useful pattern recognition to bridge the gap between purely statistical data analysis and physics-driven interpretation of the ocean acoustics that create the multipath channel delay spread. Beyond underwater acoustics, these feature learning techniques are broadly applicable to any paradigms where spectral features may evolve and intersect.

Download or read book Analysis of and Techniques for Adaptive Equalization for Underwater Acoustic Communication written by Ballard Justin Smith Blair and published by . This book was released on 2011 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt: Underwater wireless communication is quickly becoming a necessity for applications in ocean science, defense, and homeland security. Acoustics remains the only practical means of accomplishing long-range communication in the ocean. The acoustic communication channel is fraught with difficulties including limited available bandwidth, long delay-spread, time-variability, and Doppler spreading. These difficulties reduce the reliability of the communication system and make high data-rate communication challenging. Adaptive decision feedback equalization is a common method to compensate for distortions introduced by the underwater acoustic channel. Limited work has been done thus far to introduce the physics of the underwater channel into improving and better understanding the operation of a decision feedback equalizer. This thesis examines how to use physical models to improve the reliability and reduce the computational complexity of the decision feedback equalizer. The specific topics covered by this work are: how to handle channel estimation errors for the time varying channel, how to use angular constraints imposed by the environment into an array receiver, what happens when there is a mismatch between the true channel order and the estimated channel order, and why there is a performance difference between the direct adaptation and channel estimation based methods for computing the equalizer coefficients. For each of these topics, algorithms are provided that help create a more robust equalizer with lower computational complexity for the underwater channel.

Download or read book Analysis Simulation of the Deep Sea Acoustic Channel for Sensor Networks written by Anuj Sehgal and published by Lulu.com. This book was released on 2013-11-22 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt: [Color Edition]In order to examine the practices used by underwater sensor networks for successful off-shore deep sea deployments this book analyzes the underwater channel acoustic propagation model and also looks briefly at the characteristics of the underwater transducers along with the unique effect that they pose upon sonar based communication systems. The book then goes on to exploring the state of the art in underwater sensor network design paradigms followed by an analysis of areas that warrant research. A discussion on simulating such networks and an analysis of the characteristics of the underwater acoustic channel is also carried out.

Download or read book Cooperative OFDM Underwater Acoustic Communications written by Xilin Cheng and published by Springer. This book was released on 2016-06-03 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt: Following underwater acoustic channel modeling, this book investigates the relationship between coherence time and transmission distances. It considers the power allocation issues of two typical transmission scenarios, namely short-range transmission and medium-long range transmission. For the former scenario, an adaptive system is developed based on instantaneous channel state information. The primary focus is on cooperative dual-hop orthogonal frequency division multiplexing (OFDM).This book includes the decomposed fountain codes designed to enable reliable communications with higher energy efficiency. It covers the Doppler Effect, which improves packet transmission reliability for effective low-complexity mirror-mapping-based intercarrier interference cancellation schemes capable of suppressing the intercarrier interference power level. Designed for professionals and researchers in the field of underwater acoustic communications, this book is also suitable for advanced-level students in electrical engineering or computer science.

Download or read book Machine Learning and Intelligent Communications written by Huang Xin-lin and published by Springer. This book was released on 2017-01-27 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed post-conference proceedings of the International Conference on Machine Learning and Intelligent Communications, MLICOM 2016, held in Shanghai, China in August 2016. The 41 revised full papers were carefully reviewed and selected from 47 submissions. The papers are organized thematically: data mining in heterogeneous networks, decentralized learning for wireless communication systems, intelligent cooperative/distributed coding, intelligent cooperative networks, Intelligent massive MIMO, time coded multi-user MIMO System based on three dimensional complementary codes, intelligent positioning and navigation systems, intelligent spectrum allocation schemes, machine learning algorithm & cognitive radio networks, machine learning for multimedia.

Download or read book The 6th International Conference on Wireless Intelligent and Distributed Environment for Communication written by Isaac Woungang and published by Springer Nature. This book was released on 2023-12-20 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the proceedings of the 6th International Conference on Wireless Intelligent and Distributed Environment for Communication (WIDECOM 2023), which took place at Brock University, St. Catharines, Ontario, Canada, October 11-13, 2023. The book addresses issues related to new dependability paradigms, design, and performance of dependable network computing and mobile systems, as well as issues related to the security of these systems. The goal of the conference is to provide a forum for researchers, students, scientists and engineers working in academia and industry to share their experiences, new ideas and research results in the above-mentioned areas.

Download or read book Analysis Simulation of the Deep Sea Acoustic Channel for Sensor Networks written by Anuj Sehgal and published by Lulu.com. This book was released on 2013-11-21 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt: [B&W Edition] In order to examine the practices used by underwater sensor networks for successful off-shore deep sea deployments this book analyzes the underwater channel acoustic propagation model and also looks briefly at the characteristics of the underwater transducers along with the unique effect that they pose upon sonar based communication systems. The book then goes on to exploring the state of the art in underwater sensor network design paradigms followed by an analysis of areas that warrant research. A discussion on simulating such networks and an analysis of the characteristics of the underwater acoustic channel is also carried out.

Download or read book Channel Modeling and Threshold Signal Processing in Underwater Acoustics written by David Middleton and published by . This book was released on 1986 with total page 106 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Channel Modeling Method for Underwater Acoustic Digital Communications written by Thomas J. Pastore and published by . This book was released on 1992 with total page 98 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Underwater Acoustic Digital Signal Processing and Communication Systems written by Robert Istepanian and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: Underwater acoustic digital signal processing and communications is an area of applied research that has witnessed major advances over the past decade. Rapid developments in this area were made possible by the use of powerful digital signal processors (DSPs) whose speed, computational power and portability allowed efficient implementation of complex signal processing algorithms and experimental demonstration of their performance in a variety of underwater environments. The early results served as a motivation for the development of new and improved signal processing methods for underwater applications, which today range from classical of autonomous underwater vehicles and sonar signal processing, to remote control underwater wireless communications. This book presents the diverse areas of underwater acoustic signal processing and communication systems through a collection of contributions from prominent researchers in these areas. Their results, both new and those published over the past few years, have been assembled to provide what we hope is a comprehensive overview of the recent developments in the field. The book is intended for a general audience of researchers, engineers and students working in the areas of underwater acoustic signal processing. It requires the reader to have a basic understanding of the digital signal processing concepts. Each topic is treated from a theoretical perspective, followed by practical implementation details. We hope that the book can serve both as a study text and an academic reference.

Download or read book Novel Adaptive Signal Processing Techniques for Underwater Acoustic Communications written by and published by . This book was released on 2011 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Cognitive Underwater Acoustic Networking Techniques written by Dimitri Sotnik and published by Springer Nature. This book was released on 2020-09-29 with total page 89 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book summarizes the latest research on cognitive network-layer methods and smart adaptive physical-layer methods in underwater networks. Underwater communication requires extendable and delay-tolerant underwater acoustic networks capable of supporting multiple frequency bands, data rates and transmission ranges. The book also discusses a suitable foreground communication stack for mixed mobile/static networks, a technology that requires adaptive physical layer waveforms and cognitive network strategies with underlying cooperative and non-cooperative robust processes. The goal is to arrive at a universally applicable standard in the area of Underwater Internet-of-Things [ISO/IEC 30140, 30142, 30143]. The book is the second spin-off of the research project RACUN, after the first RACUN-book "Underwater Acoustic Networking Techniques" (https://link.springer.com/book/10.1007%2F978-3-642-25224-2)

Download or read book Underwater Acoustic Sensor Networks written by Yang Xiao and published by CRC Press. This book was released on 2010-05-19 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: A detailed review of underwater channel characteristics, Underwater Acoustic Sensor Networks investigates the fundamental aspects of underwater communication. Prominent researchers from around the world consider contemporary challenges in the development of underwater acoustic sensor networks (UW-ASNs) and introduce a cross-layer approach for effec