James C. Preisig

Underwater acoustic communication channels: Propagation models and statistical characterization

Acoustic propagation is characterized by three major factors: attenuation that increases with signal frequency, time-varying multipath propagation, and low speed of sound (1500 m/s). The background noise, although often characterized as Gaussian, is not white, but has a decaying power spectral density. The channel capacity depends on the distance, and may be extremely limited. Because acoustic propagation is best supported at low frequencies, although the total available bandwidth may be low, an acoustic communication system is inherently wideband in the sense that the bandwidth is not negligible with respect to its center frequency. The channel can have a sparse impulse response, where each physical path acts as a time-varying low-pass filter, and motion introduces additional Doppler spreading and shifting. Surface waves, internal turbulence, fluctuations in the sound speed, and other small-scale phenomena contribute to random signal variations. At this time, there are no standardized models for the acoustic channel fading, and experimental measurements are often made to assess the statistical properties of the channel in particular deployment sites.

Sparse Channel Estimation for Multicarrier Underwater Acoustic Communication: From Subspace Methods to Compressed Sensing

In this paper, we present various channel estimators that exploit the channel sparsity in a multicarrier underwater acoustic system, including subspace algorithms from the array precessing literature, namely root-MUSIC and ESPRIT, and recent compressed sensing algorithms in form of Orthogonal Matching Pursuit (OMP) and Basis Pursuit (BP). Numerical simulation and experimental data of an OFDM block-by-block receiver are used to evaluate the proposed algorithms in comparison to the conventional least-squares (LS) channel estimator. We observe that subspace methods can tolerate small to moderate Doppler effects, and outperform the LS approach when the channel is indeed sparse. On the other hand, compressed sensing algorithms uniformly outperform the LS and subspace methods. Coupled with a channel equalizer mitigating intercarrier interference, the compressed sensing algorithms can handle channels with significant Doppler spread.

Estimation of Rapidly Time-Varying Sparse Channels

The estimation of sparse shallow-water acoustic communication channels and the impact of estimation performance on the equalization of phase coherent communication signals are investigated. Given sufficiently wide transmission bandwidth, the impulse response of the shallow-water acoustic channel is often sparse as the multipath arrivals become resolvable. In the presence of significant surface waves, the multipath arrivals associated with surface scattering fluctuate rapidly over time, in the sense that the complex gain, the arrival time, and the Dopplers of each arrival all change dynamically. A sparse channel estimation technique is developed based on the delay-Doppler-spread function representation of the channel. The delay-Doppler-spread function may be considered as a first-order approximation to the rapidly time-varying channel in which each channel component is associated with Doppler shifts that are assumed constant over an averaging interval. The sparse structure of the delay-Doppler-spread function is then exploited by sequentially choosing the dominant components that minimize a least squares error. The advantage of this approach is that it captures both the channel structure as well as its dynamics without the need of explicit dynamic channel modeling. As the symbols are populated with the sample Dopplers, the increase in complexity depends on the channel Doppler spread and can be significant for a severely Doppler-spread channel. Comparison is made between nonsparse recursive least squares (RLS) channel estimation, sparse channel impulse response estimation, and estimation using the proposed approach. The results are demonstrated using experimental data. In training mode, the proposed approach shows a 3-dB reduction in signal prediction error. In decision-directed mode, it improves significantly the robustness of the performance of the channel-estimate-based equalizer against rapid channel fluctuations.

Communication over Doppler spread channels. Part I: Channel and receiver presentation

Scattering functions from several experiments demonstrate that acoustic underwater channels are doubly spread. Receivers used on these channels to date have difficulty with large Doppler spreads. A receiver to perform coherent communication over Doppler spread channels is presented in this first paper of two. The receiver contains a channel tracker and a linear decoder. The tracker operates by means of a modified recursive least squares algorithm which makes use of frequency-domain filters called Doppler lines. The decoder makes use of the channel tracker coefficients in order to perform minimum mean square error decoding. This first paper treats theoretical aspects whereas the second part presents implementation issues and results.

Acoustic propagation considerations for underwater acoustic communications network development

Underwater acoustic communications systems are significantly challenged by the acoustic propagation characteristics of the underwater environment. There are a wide range of physical processes that impact underwater acoustic communications and the relative importance of these processes are different in different environments. In this paper some relevant propagation phenomena are described in the context of how they impact the development and/or performance of underwater acoustic communications networks. The speed of sound and channel latency, absorption and spreading losses, waveguide effects and multipath, surface scattering, bubbles, and ambient noise are all briefly discussed.

Surface wave focusing and acoustic communications in the surf zone

The forward scattering of acoustic signals off of shoaling surface gravity waves in the surf zone results in a time-varying channel impulse response that is characterized by intense, rapidly fluctuating arrivals. In some cases, the acoustic focusing by the curvature of the wave crest results in the formation of caustics at or near a receiver location. This focusing and the resulting caustics present challenges to the reliable operation of phase coherent underwater acoustic communications systems that must implicitly or explicitly track the fluctuations in the impulse response. The propagation physics leading to focusing are studied with both experimental data and a propagation model using surface wave profiles measured during the collection of the experimental data. The deterministic experimental and modeled data show good agreement and demonstrate the stages of the focusing event and the impact of the high intensity arrivals and rapid fluctuations on the ability of an algorithm to accurately estimate the impulse response. The statistical characterization of experimental data shows that the focusing by surface gravity waves results in focused surface reflected arrivals whose intensity often exceeds that of the direct arrival and the focusing and caustic formation adversely impacts the performance of an impulse response estimation algorithm.

Performance analysis of adaptive equalization for coherent acoustic communications in the time-varying ocean environment.

Equations are derived for analyzing the performance of channel estimate based equalizers. The performance is characterized in terms of the mean squared soft decision error (sigma2(s)) of each equalizer. This error is decomposed into two components. These are the minimum achievable error (sigma2(0)) and the excess error (sigma2(e)). The former is the soft decision error that would be realized by the equalizer if the filter coefficient calculation were based upon perfect knowledge of the channel impulse response and statistics of the interfering noise field. The latter is the additional soft decision error that is realized due to errors in the estimates of these channel parameters. These expressions accurately predict the equalizer errors observed in the processing of experimental data by a channel estimate based decision feedback equalizer (DFE) and a passive time-reversal equalizer. Further expressions are presented that allow equalizer performance to be predicted given the scattering function of the acoustic channel. The analysis using these expressions yields insights into the features of surface scattering that most significantly impact equalizer performance in shallow water environments and motivates the implementation of a DFE that is robust with respect to channel estimation errors.

Optical modem technology for seafloor observatories

Regional cabled observatories will bring broadband Internet to the seafloor around areas that include hydrothermal vent sites and other scientifically interesting features. The ideal platform for exploring these sites in response to episodic events is a remotely-piloted, autonomous underwater vehicle (AUV) that is capable of sending back high-quality video or other high-rate sensor data. The combined requirement of remote command/control and high data rates argues for a bi-directional optical communications link capable of streaming data at 1-10 Mbit per second rates. In this paper, we present a preliminary design for an optical modem system based on an omnidirectional source and receiver. The functional requirements and system constraints driven by use case scenarios are first reviewed. This is followed by a discussion of the optical transmission properties of seawater and the resulting impact on detection in high-rate communications, including coding considerations. A link budget and the data rate versus range relationship are developed. Validation results in a test tank and in the ocean will then be reviewed

Coupled acoustic mode propagation through continental-shelf internal solitary waves

Three techniques are used to investigate mode coupling as acoustic energy passes through continental-shelf internal solitary waves (ISWs). Results from all techniques agree. The waves considered here are single downward undulations of a thermocline layer separating upper and lower well-mixed layers. Two techniques are numerical: parabolic equation (PE) solution and a sudden approximation joining range-invariant regions at sharp vertical interfaces. The third technique is an analytic derivation of ISW scale lengths separating adiabatic (at large scale) and coupled-mode propagation. Results show that energy is exchanged between modes as ISWs are traversed. The sharp interface solutions help explain this in terms of spatially confined coupling and modal phase interference. Three regimes are observed: 1) for short ISWs, coupling upon wave entrance is reversed upon exit, with no net coupling; 2) for ISW scales of 75-200 m, modal phase alteration averts the exit reversal, giving net coupling; transparent resonances yielding no net coupling are also observed in this regime; and 3) for long ISWs, adiabaticity is probable but not universal. Mode refraction analysis for nonparallel acoustic-ISW alignment suggests that these two-dimensional techniques remain valid for 0/spl deg/ (parallel) to 65/spl deg/ (oblique) incidence, with an accordant ISW stretching.

Sparse channel estimation for multicarrier underwater acoustic communication: From subspace methods to compressed sensing

In this paper, we present various channel estimators that exploit the channel sparsity in a multicarrier underwater acoustic system, including subspace algorithms from the array precessing literature, namely root-MUSIC and ESPRIT, and recent compressed sensing algorithms in form of Orthogonal Matching Pursuit (OMP) and Basis Pursuit (BP). Numerical simulation and experimental data of an OFDM block-by-block receiver are used to evaluate the proposed algorithms in comparison to the conventional least-squares (LS) channel estimator. We observe that subspace methods can tolerate small to moderate Doppler effects, and outperform the LS approach when the channel is indeed sparse. On the other hand, compressed sensing algorithms uniformly outperform the LS and subspace methods. Coupled with a channel equalizer mitigating intercarrier interference, the compressed sensing algorithms can handle channels with significant Doppler spread.