Application Of Spatial Modulation To The Underwater Acoustic Communication Component Of Autonomous Underwater Vehicle Networks
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| Author | : |
| Publisher | : |
| Total Pages | : 8 |
| Release | : 2005 |
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There have been two fundamental advances in underwater acoustic communication in the last two decades. The first occurred in the early 1980's with the introduction of digital signaling techniques 1. That facilitated both error correction and reverberation mitigation. The second advance has been the successful application of coherent signaling techniques 2. That facilitated dramatic improvements in bandwidth efficiency and, hence, data rates. Since the introduction of coherent systems in the early 1990's, however, performance gains have been moderate and mostly attributed to important but largely technical algorithm improvements 3. Spatial modulation offers the hope of yet another fundamental advance in performance by both enabling higher data rates and offering a strategy for improving performance in intersymbol interference (ISI) limited channels. The research conducted in this program seeks to define both the potential for spatial modulation in U.S. Navy underwater communication systems and develop practical prototypes suitable to meet U.S. Navy needs.
| Author | : Daniel B. Kilfoyle |
| Publisher | : |
| Total Pages | : 428 |
| Release | : 2000 |
| Genre | : Modulation (Electronics) |
| ISBN | : |
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.
| Author | : Baosheng Li |
| Publisher | : |
| Total Pages | : 174 |
| Release | : 2009 |
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| Author | : Jing Yan |
| Publisher | : Springer Nature |
| Total Pages | : 222 |
| Release | : 2021-11-01 |
| Genre | : Technology & Engineering |
| ISBN | : 9811660964 |
Autonomous underwater vehicles (AUVs) are emerging as a promising solution to help us explore and understand the ocean. The global market for AUVs is predicted to grow from 638 million dollars in 2020 to 1,638 million dollars by 2025 – a compound annual growth rate of 20.8 percent. To make AUVs suitable for a wider range of application-specific missions, it is necessary to deploy multiple AUVs to cooperatively perform the localization, tracking and formation tasks. However, weak underwater acoustic communication and the model uncertainty of AUVs make achieving this challenging. This book presents cutting-edge results regarding localization, tracking and formation for AUVs, highlighting the latest research on commonly encountered AUV systems. It also showcases several joint localization and tracking solutions for AUVs. Lastly, it discusses future research directions and provides guidance on the design of future localization, tracking and formation schemes for AUVs. Representing a substantial contribution to nonlinear system theory, robotic control theory, and underwater acoustic communication system, this book will appeal to university researchers, scientists, engineers, and graduate students in control theory and control engineering who wish to learn about the core principles, methods, algorithms, and applications of AUVs. Moreover, the practical localization, tracking and formation schemes presented provide guidance on exploring the ocean. The book is intended for those with an understanding of nonlinear system theory, robotic control theory, and underwater acoustic communication systems.
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| Publisher | : |
| Total Pages | : 21 |
| Release | : 2004 |
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Multiple-input multiple-output (MIMO) communication channels are an active area of research for terrestrial wireless applications. The natural bandwidth limitations of the underwater acoustic channel (UAC) combined with the potential for a rich spatial propagation structure suggest the ocean may be another useful application area for MIMO techniques. An underwater acoustic communications experiment was conducted in the waters surrounding Elba, Italy, using spatially modulated signals. Two frequency regimes (9.5-14.5 kHz and 25-35 kHz) were explored over ranges up to 5 km using vertical line arrays suspended from drifting ships. The UAC had an average depth of 100 m. One-way communication links were established at two sites with one site having a rocky (reverberant) bottom and the other having a muddy (absorbent) bottom. The waveform comprised a single data stream with concatenated codes providing error control. The inner code was a high rate BCH code Trellis-coded modulation was used as the basis for the outer code. Successive coded symbols were multiplexed across the available transducer elements. This coding approach effectively maintains the inherent bandwidth efficiency of MIMO signaling. The receiver was an adaptive recursively updated multichannel decision feedback equalizer operating in conjunction with a digital phase-locked loop A packet-based, transport architecture was used and included a training sequence. A Viterbi algorithm was integrated with the equalizer that supported simultaneous tap-weight update and trellis transversal, thereby affording the decision-directed update partial error control. Using appropriate assumptions, channel capacity using a single transducer was estimated to be 5.4 bits/channel use at the soft bottom site. Capacity was maximized at 15.9 bits/channel use using four transducers. More detailed results will be presented along with performance predictions based on both propagation models and measured channel transfer functions7.
| Author | : Gwyn Griffiths |
| Publisher | : CRC Press |
| Total Pages | : 369 |
| Release | : 2002-11-28 |
| Genre | : Technology & Engineering |
| ISBN | : 0203522303 |
The oceans are a hostile environment, and gathering information on deep-sea life and the seabed is incredibly difficult. Autonomous underwater vehicles are robot submarines that are revolutionizing the way in which researchers and industry obtain data. Advances in technology have resulted in capable vehicles that have made new discoveries on how th
| Author | : Robert Istepanian |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 283 |
| Release | : 2013-03-09 |
| Genre | : Technology & Engineering |
| ISBN | : 1475736177 |
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.
| Author | : Fei Hu |
| Publisher | : CRC Press |
| Total Pages | : 357 |
| Release | : 2023-05-12 |
| Genre | : Computers |
| ISBN | : 100087723X |
Deep Learning (DL) is an effective approach for AI-based vehicular networks and can deliver a powerful set of tools for such vehicular network dynamics. In various domains of vehicular networks, DL can be used for learning-based channel estimation, traffic flow prediction, vehicle trajectory prediction, location-prediction-based scheduling and routing, intelligent network congestion control mechanism, smart load balancing and vertical handoff control, intelligent network security strategies, virtual smart and efficient resource allocation and intelligent distributed resource allocation methods. This book is based on the work from world-famous experts on the application of DL for vehicle networks. It consists of the following five parts: (I) DL for vehicle safety and security: This part covers the use of DL algorithms for vehicle safety or security. (II) DL for effective vehicle communications: Vehicle networks consist of vehicle-to-vehicle and vehicle-to-roadside communications. This part covers how Intelligent vehicle networks require a flexible selection of the best path across all vehicles, adaptive sending rate control based on bandwidth availability and timely data downloads from a roadside base-station. (III) DL for vehicle control: The myriad operations that require intelligent control for each individual vehicle are discussed in this part. This also includes emission control, which is based on the road traffic situation, the charging pile load is predicted through DL andvehicle speed adjustments based on the camera-captured image analysis. (IV) DL for information management: This part covers some intelligent information collection and understanding. We can use DL for energy-saving vehicle trajectory control based on the road traffic situation and given destination information; we can also natural language processing based on DL algorithm for automatic internet of things (IoT) search during driving. (V) Other applications. This part introduces the use of DL models for other vehicle controls. Autonomous vehicles are becoming more and more popular in society. The DL and its variants will play greater roles in cognitive vehicle communications and control. Other machine learning models such as deep reinforcement learning will also facilitate intelligent vehicle behavior understanding and adjustment. This book will become a valuable reference to your understanding of this critical field.
| Author | : Tien Anh Tran |
| Publisher | : CRC Press |
| Total Pages | : 191 |
| Release | : 2023-12-04 |
| Genre | : Technology & Engineering |
| ISBN | : 1003817025 |
The development of intelligent transportation systems, especially autonomous underwater vehicles, has become significant in marine engineering, with an aim to enhance energy efficiency management and communication systems. This book covers different aspects of optimization of autonomous underwater vehicles and their propulsion systems via machine learning techniques. It further analyses hydrodynamic characteristics including the study of experimental investigation combined with hydrodynamic characteristics backed by MATLAB® codes and simulation study results. Features: Covers utilization of machine learning techniques with a focus on marine science and ocean engineering. Details effect of the intelligent transportation system (ITS) into the sustainable environment and ecology system. Evaluates performance of particle swarm intelligence-based optimization techniques. Reviews propulsion performance of the remote-controlled vehicles based on machine learning techniques. Includes MATLAB® examples and simulation study results. This book is aimed at graduate students and researchers in marine engineering and technology, computer science, and control system engineering.
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| Total Pages | : |
| Release | : 2018 |
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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.
