The extreme and uncertain underwater environment presents significant challenges in achieving reliable acoustic communications, mainly due to limited bandwidth and time variability. To address these challenges, this work proposes a novel multiple-access technique for downlink multiuser networks, called Orthogonal Signal Division Multiple Access (OSDMA), which enables simultaneous transmission of different data streams from a single transmitter to the corresponding receivers/users by modulating the streams with an orthogonal Inverse Discrete Fourier Transform (IDFT) matrix. In a low-noise environment, each receiver/user can accurately estimate the channel and demodulate the data. Emulations and simulations are conducted based on at-sea channel measurements. The results show that OSDMA offers greater robustness against underwater time-varying channels than Orthogonal Frequency Division Multiple Access (OFDMA) and Non-Orthogonal Multiple Access (NOMA).

Underwater communications suffer from numerous challenges typically associated with relevant signal attenuation, long propagation delay, limited available bandwidth, and high error rates that severely affect underwater transmission performance. Therefore, it is crucial to apply adaptive or predictive techniques to ensure the best possible performance and guarantee reliability in underwater communication, especially in rapidly changing environments. Using adaptive (i.e., reactive) or predictive (i.e., proactive) methods, it is possible to avoid data retransmission, improve the lifetime of underwater nodes, reduce maintenance frequency and the necessary equipment replacement and recharge, and consequently optimize performance in general. In this regard, many works in the literature propose various adaptive or predictive techniques for UnderWater Acoustic (UWA) networks, which we critically classify and discuss in this qualitative survey.

Achieving reliable underwater acoustic communications is a challenging task due to the time-varying channels in the underwater acoustic environment. Scalable Video Coding (SVC) has been widely used in video transmissions. However, inappropriate SVC structures can lead to poorer received video quality than user requirements 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 Receiver-Driven Adaptive Scalable Video Transmission (RD-ASVTuw). In RD-ASVTuw, the decision-making about transmission schemes takes place at the receiver through Machine Learning (ML). The transmitter collects over time the selected transmission scheme indexes and the user’s video quality requirements to transmit the SVC video adaptively. At-sea experiments were conducted to collect the required acoustic data. The data collected were then used in MATLAB simulations to validate RD-ASVTuw.

Reliable and persistent water monitoring is a challenging problem in smart underwater Internet of Things (UW IoT) due to its harsh, unexplored, and unpredictable nature. Given the need for high-resolution spatio–temporal sensing in such environments, traditional digital sensors are not suitable due to their high-cost, high-power consumption, and nonbiodegradable nature. Further, reliable and low-latency communication techniques that avoid data packet retransmissions, if the feedback is available, are crucial for reconstructing the phenomenon being monitored in a timely manner at the fusion center, such as a drone. To address the above challenges, we propose a novel architecture consisting of a substrate of densely deployed underwater all-analog biodegradable sensors that enable persistent sensing and continually transmitting data to the surface digital buoys. The analog nodes are designed to be energy efficient by implementing analog joint source-channel coding (JSCC), a low-complexity compression-communication technique, using biodegradable field effect transistors (FETs). We, then, propose a correlation-aware hybrid automatic repeat request (HARQ) technique to transmit data from the surface buoys to the fusion center. Such HARQ technique leverages JSCC and the redundancy in the buoy data (arising from the correlation of the phenomenon at the analog nodes) to avoid retransmissions, thus, saving energy and time.

An underwater wireless optical communication link can provide high-speed data transfer for robotics applications in deep waters. However, optical links are limited in terms of coverage range because of the high attenuation of light in water caused by absorption and scattering effects. In this work, a new optical transceiver architecture is proposed to solve this coverage problem via a novel Orthogonal Frequency Division Multiplexing (OFDM)-based Polarized Pulse Position Modulation (in short, P-OFDM-PPM) with time-frequency spreading. The optical polarization diversity and multiplexing are utilized at the optical transmitter to improve the system’s robustness and the transmission data rate. This new scheme is able to boost the range coverage by several folds as verified via simulations using realistic models of optical channel propagation. The proposed architecture can be integrated into existing underwater robots to enable next-generation range-extended and high-speed optical links for oceanic explorations.

Achieving reliable acoustic wireless video transmissionsin 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 channel state information and the robustness of different SVC scalability. The video quality level is determined by the best communication link while the transmission scheme is decided based on the worst communication link, which guarantees that each user is able to receive the video with appropriate quality.