- Award ID(s):
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- OCEANS 2018 MTS/IEEE Charleston
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- 1 to 6
- Sponsoring Org:
- National Science Foundation
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Achieving reliable acoustic wireless video transmissions in the extreme and uncertain underwater environment is a challenge due to the limited bandwidth and the error-prone nature of the channel. Aiming at optimizing the received video quality and the user's experience, an adaptive solution for underwater video transmissions is proposed that is specifically designed for Multi-Input Multi-Output (MIMO -based Software-Defined Acoustic Modems (SDAMs . To keep the video distortion under an acceptable threshold and to keep the Physical-Layer Throughput (PLT high, cross-layer techniques utilizing diversity-spatial multiplexing and Unequal Error Protection (UEP are presented along with the scalable video compression at the application layer. Specifically, the scalability of the utilized SDAM with high processing capabilities is exploited in the proposed structure along with the temporal, spatial, and quality scalability of the Scalable Video Coding (SVC H.264/MPEG-4 AVC compression standard. The transmitter broadcasts one video stream and realizes multicasting at different users. Experimental results at the Sonny Werblin Recreation Center, Rutgers University-NJ, are presented. Several scenarios for unknown channels at the transmitter are experimentally considered when the hydrophones are placed in different locations in the pool to achieve the required SVC-based video Quality of Service (QoS and Quality of Experience (QoE given the channelmore »
Scalable Video Coding (SVC) has been widely used in video transmissions. However, inappropriate SVC structures may lead to received video quality lower than user’s requirement or resource waste, especially in underwater time-varying channels. In this work, an adaptive cross-layering solution is proposed and validated for video transmissions in underwater acoustic multicast networks, namely Adaptive Scalable Video Transmission (ASVTuw). In ASVTuw, the transmitter collects over time the information about the channel states and the users’ video quality requirements to adaptively select the SVC video structures and transmission schemes, using Machine Learning (ML). At-sea experiments were conducted to collect the required acoustic data. The collected data were then used in MATLAB simulations to validate the ASVTuw. The results show that the usage of ASVTuw avoids resource wasting from transmitting redundant SVC substreams and satisfies the multicast users’ video quality requirements effectively with higher flexibility compared with the existing noncross-layering designs.
Underwater networks of wireless sensors deployed along the coast or in the deep water are the most promising solution for the development of underwater monitoring, exploration and surveillance applications. A key feature of underwater networks that can significantly enhance current monitoring applications is the ability to accommodate real-time video information on an underwater communication link. In fact, while today monitoring relies on the exchange of simple discrete information, e.g., water temperature, and particle concentration, among others, by introducing real-time streaming capability of non-static images between wireless underwater nodes one can completely revolutionize the whole underwater monitoring scenario. To achieve this goal, underwater links are required to support a sufficiently high data rate, compatible with the streaming rates of the transmitted video sequence. Unfortunately, the intrinsic characteristic of the underwater propagation medium has made this objective extremely challenging. In this paper, we present the first physical layer transmission scheme for short-range and high-data rate ultrasonic underwater communications. The proposed solution, which we will refer to as Underwater UltraSonar (U2S), is based on the idea of transmitting short information-bearing carrierless ultrasonic signals, e.g., pulses, following a pseudo-random adaptive time-hopping pattern with a superimposed rate-adaptive Reed-Solomon forward error correction (FEC) channel coding. Wemore »
Underwater acoustic (UWA) communications have attracted a lot of interest in recent years motivated by a wide range of applications including offshore oil field exploration and monitoring, oceanographic data collection, environmental monitoring, disaster prevention, and port security. Different signaling solutions have been developed to date including non‐coherent communications, phase coherent systems, multi‐input and multi‐output solutions, time‐reversal‐based communication systems, and multi‐carrier transmission approaches. This paper deviates from the traditional approaches to UWA communications and develops a scheme that exploits biomimetic signals. In the proposed scheme, a transmitter maps the information bits to the parameters of a biomimetic signal, which is transmitted over the channel. The receiver estimates the parameters of the received signal and demaps them back to bits to estimate the message. As exemplary biomimetic signals, analytical signal models with nonlinear instantaneous frequency are developed that match mammal sound signatures in the time‐frequency plane are developed. Suitable receiver structures as well as performance analysis are provided for the proposed transmission scheme, and some results using data recorded during the Kauai Acomms MURI 2011 UWA communications experiment are presented. Copyright © 2016 John Wiley & Sons, Ltd.
Achieving high throughput and reliability in underwater acoustic networks is a challenging task due to the bandwidth-limited and unpredictable nature of the channel. In a multi-node structure, such as in the Internet of Underwater Things (IoUT), the efficiency of links varies dynamically because of the channel variations. When the channel is not in good condition, e.g., when in deep fade, channel-coding techniques fail to deliver the required information even with multiple rounds of retransmissions. An efficient and agile collaborative strategy among the nodes is required to assign appropriate resources to each link based on their status and capability. Hence, a cross-layer collaborative strategy is introduced to increase the throughput of the network by allocating unequal share of system resources to different nodes/links. The proposed solution adjusts the physical- and link-layer parameters in a collaborative manner for a Code Division Multiple Access (CDMA)-based underwater network. An adaptive Hybrid Automatic Repeat Request (HARQ) solution is employed to guarantee reliable communications against errors in poor communication links. Results are being validated using data collected from the LOON underwater testbed, which is hosted by the NATO STO Centre for Maritime Research and Experimentation (CMRE) in La Spezia, Italy.