Reliable underwater acoustic video transmission towards human-robot dynamic interaction
Description
TitleReliable underwater acoustic video transmission towards human-robot dynamic interaction
Date Created2020
Other Date2020-10 (degree)
Extent1 online resource (xviii, 173 pages) : illustrations
DescriptionIn the past decade, underwater communications have enabled a wide range of applications; there are, however, novel applications and systems, such as coastal multimedia surveillance, oil pipe/bridge inspection, water-quality/marine-pollution monitoring, video monitoring of geological/biological processes from seafloor to air-sea interface, and Underwater Internet of Things (UW IoT), that require near-real-time multimedia acquisition, classification, and transmission. Wireless acoustics is the typical physical-layer communication technology for underwater data transmission for distances above a hundred meters; transmitting videos wirelessly underwater using acoustic waves, however, is a very challenging task as the underwater acoustic channel suffers from time-varying attenuation and fading, limited bandwidth, Doppler spreading, high propagation delay, and high bit error rate. For these reasons, state-of-the-art acoustic communication solutions are still mostly focusing on enabling delay-tolerant, low-bandwidth/low-data-rate scalar data transmission or at best low-quality/low-resolution multimedia streaming in the order of few tens of kbps. On the other hand, while conventional underwater acoustic modems with their fixed-hardware designs hardly meet the data rate and flexibility needed to support video requirements for futuristic multimedia and UW IoT-driven applications, novel algorithms and protocols can be implemented on reconfigurable software-defined architectures so as to perform in-network analysis and/or to transmit a high volume of data to a remote node depending on the environment and system specifications.
For these reasons, the objectives of this research, which led to this doctoral dissertation, were to propose solutions to overcome the limitations of existing acoustic communication techniques and to support robust, reliable, and high-data-rate underwater multimedia transmission. In particular, these objectives were achieved by:
- Developing a new physical-layer solution based on multiple-antenna arrays and Acoustic Vector Sensors (AVSs) and by proposing an underwater acoustic Non-Contiguous Orthogonal Frequency Division Multiplexing (NC-OFDM) technique, called Signal-Space-Frequency Beamforming (SSFB), to boost the data rate for underwater acoustic transmission so as to transfer high-resolution videos.
- Designing a probabilistic Medium Access Control (MAC) solution by introducing a novel underwater
Space Division Multiple Access (SDMA) method to share reliably the space among the steered vehicles so as to reduce the acoustic interference in underwater sparse networks.
- Improving the reliability and the quality of multimedia delivery by designing a reliable closed-loop
hybrid Automatic Repeat Request (ARQ) coding specifically designed for the harsh underwater environment, and by introducing an efficient and agile collaborative coding strategy to allocate appropriate resources to the communication links based on their status.
- Enhancing the video quality via a cross-layer design for underwater scalable coded videos that are channel compatible, and leveraging the multiplexing-diversity tradeoff in a Multiple Input Multiple Output (MIMO) structure to adjust the video scalability by trading off in real time transmission data rate and reliability according to the user Quality of Service (QoS).
- Presenting a protocol for underwater in-network imagery analysis and monitoring the accumulation
of litter and plastic debris at the seafloor using partial information collected by various vehicles around the scene, and using Scalable Video Coded (SVC) multicasting for underwater real-time map reconstruction.
- Proposing a correlation-aware hybrid ARQ technique that leverages the redundancy in the data arising from spatial and temporal correlations of the measured phenomenon; this novel technique can be used in futuristic UW IoT applications with high-density deployed nodes in shallow water.
NotePh.D.
NoteIncludes bibliographical references
Genretheses, ETD doctoral
LanguageEnglish
CollectionSchool of Graduate Studies Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.
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