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1. ASVTuw: Adaptive Scalable Video Transmission in Underwater Acoustic Multicast Networks

   https://doi.org/10.1145/3567600.3568137  

   Qi, Zhuoran; Petroccia, Roberto; Pompili, Dario (November 2022, WUWNet'22: The 16th International Conference on Underwater Networks & Systems)

   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. 

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2. Adaptive Underwater Video Transmission via Software-Defined MIMO Acoustic Modems

   https://doi.org/10.1109/OCEANS.2018.8604782  

   Rahmati, Mehdi; Gurney, Adam; Pompili, Dario (October 2018, OCEANS 2018 MTS/IEEE Charleston)

   Video signal transmission enables a wide range of applications in the underwater environment; such as coastal and tactical multimedia surveillance, undersea/offshore exploration, oil pipe/bridge inspection, video monitoring of geologica/biological processes from the seafloor to the air-sea interface-that all require real-time multimedia acquisition and classification. Yet, it is a challenge to achieve an efficient and reliable video transmission, due to the spectrum limitations underwater and also the error prone nature of the acoustic channel. In this paper, we propose a pairwise scheme to manage the video distortion-rate tradeoff for underwater video transmission. The proposed Multi-input Multi-output (MIMO)-based Software-Defined Acoustic Radio (SDAR) system adapts itself to meet the needs of both video compression and underwater channel in a timely manner from one hand, and keeps the overall video distortion-caused by the coder/decoder and channel-under an acceptable threshold from the other hand. The scalability of Universal Software Radio Peripheral (USRP) with high processing capabilities is exploited in the proposed structure along with the temporal, spatial and quality scalability of Scalable Video Coding (SVC) H.264/MPEG-4 AVC compression standard. Experimental results at Sonny Werblin Recreation Center, Rutgers University, as well as simulations are presented, while more experiments are in-progress to evaluate the performance of our testbed in more challenging environments such as in the Raritan River, New Jersey. 

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3. High-Data Rate Carrierless Impulsive Communications For Underwater Acoustic Networks

   Demirors, E.; Unal, D.; Santagati, G. E.; Melodia, T. (January 2019, Underwater Acoustics Conference and Exhibition)

   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. We also present the design of the first prototype of a software-defined underwater ultrasonic transceiver that implements U2S PHY transmission scheme through which we evaluate the U2S performance in real-scenario underwater experiments at the PHY layer, i.e., Bit Error Rate (BER) extensively, and at the application layer, i.e., structural similarity (SSIM) index. Results show that U2S links can support point-to-point data rate up to 1.38 Mbps and that by leveraging the flexibility of the adaptive time-hopping and adaptive channel coding techniques, one can trade between link throughput and energy consumption, still satisfying application layer requirements. 

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4. Performance Prediction of Underwater Acoustic Communications Based on Channel Impulse Responses

   https://doi.org/10.3390/app12031086  

   Lucas, Evan; Wang, Zhaohui (February 2022, Applied Sciences)

   Predicting the channel quality for an underwater acoustic communication link is not a straightforward task. Previous approaches have focused on either physical observations of weather or engineered signal features, some of which require substantial processing to obtain. This work applies a convolutional neural network to the channel impulse responses, allowing the network to learn the features that are useful in predicting the channel quality. Results obtained are comparable or better than conventional supervised learning models, depending on the dataset. The universality of the learned features is also demonstrated by strong prediction performance when transferring from a more complex underwater acoustic channel to a simpler one. 

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5. Optical Focusing-Based Adaptive Modulation for Air-to-Underwater Optoacoustic Communication

   https://doi.org/10.1109/JSEN.2023.3340092  

   Mahmud, Muntasir; Younis, Mohamed; Choa, Fow-Sen; Ahmed, Akram (March 2024, IEEE Sensors Journal)

   Nonlinear optoacoustics enable effective communication across the air-water interface. However, the requirement of a high-power laser and the vapor cloud buildup can limit the power efficiency and data rate. Thus, a proper modulation and encoding scheme is necessary. This article tackles this issue by presenting an optical focusing-based adaptive modulation (OFAM) technique that can dynamically control the underwater acoustic source (plasma) and acoustic pressure. Specifically, the article describes two variants of OFAM for a single laser transmitter with stationary focusing (OFAM-1D) and dynamic focusing (OFAM-3D). The data rate of OFAM-1D and OFAM-3D is approximately 6 and 4.4 times higher than peak detection based on-off keying (PDOOK). Furthermore, both techniques are 137% more power efficient than PDOOK. Studying the bit error rate (BER) in the presence of ambient underwater noises for different node positions has indicated that OFAM can achieve low BER even at a 300-m depth for 50- and 60-mJ laser pulse energy. Moreover, machine learning (ML) techniques have been leveraged in the demodulation process for increased robustness. Specifically, the random forest (RF) model could yield up to 94.75% demodulation accuracy. Our results indicate that OFAM can lead to a new paradigm of air to underwater wireless communication. 

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