Paul A. van Walree

Underwater acoustic data communication is an enabling technology for operations such as environmental monitoring, exploitation of ocean resources, and autonomous inspection of offshore infrastructure. The only viable technique for subsea telemetry over longer distances is by encoding the information in sound waves. However, the influence of the ocean environment on sound propagation can be harsh, resulting in a poor performance of protocols designed for terrestrial radio-frequency communications. This justifies active research on physical-layer algorithms and network protocols that are robust to acoustic propagation in the oceans. Factors that hamper progress are the lack of accepted standard test channels and hard-to-obtain field data. A majority of academic institutions cannot afford at-sea experimentation, resorting to simplified channel models to test new protocols. In order to make field data accessible to a wider audience, this paper presents a dataset of hydrophone recordings of communication and channel probe waveforms collected in an enclosed fjord environment. The SFI Smart Ocean Dataset for Acoustic Communications (SODAC) allows users to test communication algorithms on in situ data, with opportunities to publish reproducible results that set a realistic benchmark for other researchers.

The rapid growth of marine industries has emphasized the focus on environmental impacts for all industries, as well as the influence of key environmental parameters on, for instance, offshore wind or aquaculture performance, animal welfare and structural integrity of different constructions. Development of automatized sensors together with efficient communication and information systems will enhance surveillance and monitoring of environmental processes and impact. We have developed a modular Smart Ocean observatory, in this case connected to a large-scale marine aquaculture research facility. The first sensor rigs have been operational since May 2022, transmitting environmental data in near real-time. Key components are Acoustic Doppler Current Profilers (ADCPs) for measuring directional wave and current parameters, and CTDs for redundant measurement of depth, temperature, conductivity and oxygen. Communication is through 4G network or cable. However, a key purpose of the observatory is also to facilitate experiments with acoustic wireless underwater communication, which are ongoing. The aim is to expand the system(s) with demersal independent sensor nodes communicating through an “Internet of Underwater Things (IoUT)”, covering larger areas in the coastal zone, as well as open waters, of benefit to all ocean industries. The observatory also hosts experiments for sensor development, biofouling control and strategies for sensor self-validation and diagnostics. The close interactions between the experiments and the infrastructure development allow a holistic approach towards environmental monitoring across sectors and industries, plus to reduce the carbon footprint of ocean observation. This work is intended to lay a basis for sophisticated use of smart sensors with communication systems in long-term autonomous operation in remote as well as nearshore locations.

This article describes a field-programmable gate array (FPGA) based multihydrophone receiver, and evaluates its real-time performance in various shallow-water channels. The receiver, built around an integer precision multichannel linear equalizer, uses the Least Mean Squares Algorithm for filter tap updates. Combined with a 64-hydrophone line array in the very high-frequency band, the receiver achieves information data rates up to 465 kb/s over 100 m, and rates up to 155 kb/s over 1000 m.

This paper presents data from mid-frequency (4–8 kHz) under-ice acoustic transmission and communication experiments in the Nansen Basin and in the Beaufort Sea of the Arctic Ocean. Measured impulse responses to range ∼10 km showed considerable delay spread between distinct groups of arrivals due to surface-ducted and bottom-reflected paths. The relative strengths of these groups depend on duct and under-ice properties. We demonstrate that despite shallow (∼25 m) source/receiver depths, good communication performance can be achieved in both environments when exploiting the bottom-reflected arrivals. Simulations with the Bellhop ray model support the findings.

A channel sounding and communications experiment was performed in the Oslofjord, using eight bottom-mounted instrument units deployed in a network configuration. Five units were equipped with a software-defined 4–8-kHz acoustic modem, programmed to transmit probe signals and communication packets in a round-robin fashion. All transmitted waveforms were recorded by all units over 35 horizontal links and 5 vertical links. The channels reveal a reverberant environment with long and dense multipath arrival patterns. Measured power-delay profiles and delay-Doppler spread functions are used to predict receiver output signal-to-noise ratio (SNR) over a signaling period of 26 h. To this end, the channel quantities are first calibrated for the propagation loss. The prediction examines the effect of ambient noise, reverberation of previously transmitted packets, the packet’s own reverberation, and Doppler spread. The delay profile can be used under calm conditions, and results in a mean prediction error (averaged over all links) of about 3 dB, even hours after the measurement of the profiles. The mean error on individual links (averaged over time) is reduced to 1–2 dB by using up-to-date channel information. The relevance of predicting output SNR is finally illustrated by establishing a relationship between output SNR and the probabilities of bit and packet error.

There is an expected growth in underwater acoustic data traffic. To meet the demand of high data throughput, a migration towards the very high frequency band (>100 kHz) will be necessary. The increment in frequency comes with two problems; high propagation losses and rapid channel fluctuations. One solution addressing both of these obstacles is the use of large hydrophone arrays in combination with multi-channel equalizers. We will in this paper examine and compare tracking properties and convergence rate of the RLS and LMS adaptive algorithm for use in large multichannel equalizers. Using data from a very high frequency (250 kHz) channel we will show that in our channel, for large hydrophone arrays, RLS does not offers a significant advantage over LMS when it comes to tracking channel variations nor convergence rate.

Watermark is a freely available benchmark for physical-layer schemes for underwater acoustic communications. It allows researchers to test and compare algorithms for the physical layer under realistic and reproducible conditions. The benchmark is a shell around the validated channel simulator Mime, which is driven by at-sea measurements of the time-varying impulse response. The first release of Watermark is issued with a library of channels measured in Norway (two sites), France, and Hawaii, offering three frequency bands (4–8, 10–18, and 32.5–37.5 kHz), single-hydrophone and array receivers, and play times varying from 33 s to 33 min.

Watermark is a benchmark for testing, development, and comparison of physical-layer schemes for underwater acoustic communications. Its core is a replay channel simulator driven by at-sea measurements of the time-varying impulse response. Watermark is programmed in MATLAB and is initially provided with two (single-receiver) test channels with a run time of 30 minutes each. These channels were measured in Norwegian waters in the frequency band from 10 to 18 kHz. The benchmark can be extended with channels from different environments and frequency bands, depending on the willingness of third parties to perform and make available such measurements.