Simulation forms an important part of the development and empirical evaluation of underwater acoustic network (UAN) protocols. The key feature of a credible network simulation model is a realistic channel model. A common approach to simulating realistic underwater acoustic (UWA) channels is by using specialised beam tracing software such as BELLHOP. However, BELLHOP and similar modeling software typically require knowledge of ocean acoustics and a substantial programming effort from UAN protocol designers to integrate it into their research. This paper is a distilled tutorial on UWA channel modeling with a focus on network simulation, providing a trade-off between the flexibility of low level channel modeling via beam tracing and the convenience of automated channel modeling, e.g. via the World Ocean Simulation System (WOSS). The tutorial is accompanied by our MATLAB simulation code that interfaces with BELLHOP to produce channel data for UAN simulations. As part of the tutorial, we describe two methods of incorporating such channel data into network simulations, including a case study for each of them: 1) directly importing the data as a look-up table, 2) using the data to create a statistical channel model. The primary aim of this paper is to provide a useful learning resource and modeling tool for UAN protocol researchers. Initial insights into the UAN protocol design and performance provided by the statistical channel modeling approach presented in this paper demonstrate its potential as a powerful modeling tool for future UAN research.

Underwater acoustic (UWA) communication suffers from the limited available bandwidth for data transmission. Full-duplex (FD) communication has demonstrated the ability of achieving high spectral efficiency in terrestrial radio communications. There is a significant potential in adopting the benefits of FD in UWA systems. The major obstacle in FD communications is the severe self-interference (SI) introduced by the near-end transmitted signal. For FD UWA communications, the low signal frequency allows high-resolution ADCs to be used. With higher performance ADCs, it might be possible to achieve higher digital SI cancellation performance than that in FD radio systems. In this paper, we present experimental results of digital SI cancellation in FD UWA system, based on the use of the low-complexity recursive least-squares (RLS) adaptive filter with dichotomous coordinate descent iterations. The experimental results demonstrate that up to 46 dB of SI is cancelled when we use the transmitted digital data as the regressor in the adaptive filter. To improve the SI cancellation performance without introducing high-complexity operation, we use the digitalized power amplifier (PA) output as the regressor to deal with the non-linear distortions caused by the PA in the transmitted chain. With this technique, as high a level as 69 dB of digital SI cancellation is achieved.

To enable full-duplex (FD) in underwater acoustic (UWA) systems, a high level of self-interference cancellation (SIC) is required. This can be achieved by using a combination of SIC methods, including digital SIC. For digital SIC, adaptive filters are used. In time-invariant channels, the SI can be effectively cancelled by classical recursive least-square (RLS) adaptive filters, such as the sliding-window RLS (SRLS) or exponential-window RLS, but their SIC performance degrades in time-varying channels, e.g., in channels with a moving sea surface. Their performance can be improved by delaying the filter inputs. This delay, however, makes the mean squared error (MSE) unsuitable for measuring the SIC performance. In this article, we propose a new evaluation metric, the SIC factor (SICF), which gives better indication of the SIC performance compared to MSE. The SICF can be used to evaluate the performance of digital SIC techniques without the need of implementing a full FD system. A new SRLS adaptive filter based on parabolic approximation of the channel variation in time, named SRLS-P, is also proposed. The SIC performance of the SRLS-P adaptive filter and classical RLS algorithms (with and without the delay) is evaluated by simulation and in lake experiments. The results show that the SRLS-P adaptive filter can significantly improve the SIC performance, compared to the classical RLS adaptive filters.

The maximum correntropy criterion (MCC) algorithm depends upon two fundamental parameters, i.e., step-size and kernel width. Previous studies of parameter optimization in the MCC mainly focus on a single parameter (mainly the kernel width), lacking optimization research concerning both parameters. To this end, this letter investigates a novel optimization scheme simultaneously involving step-size and kernel width. The optimization framework is based on making the power of weight error vector undergo the steepest attenuation. Under the premise of maintaining the same evolutionary trend for time-varying step-size and kernel width, we formulate a constrained parameter optimization problem, where the step-size is subject to a kernel width induced constraint. By taking this approach, the original bivariate optimization can be transformed into a univariate optimization problem, which facilitates optimization solving. We further develop an existing reset scheme to make it suitable for kernel width to ensure a good tracking capability. In addition, we investigate the convergence behavior of the optimized algorithm. Simulation results demonstrate that the developed optimization scheme is beneficial for performance improvement, and the resulting algorithm outperforms some state-of-art MCC-based algorithms.

To enable full-duplex (FD) operation in underwater acoustic systems, the strong self-interference (SI) from the near-end transmitter should be efficiently cancelled. Digital cancellation is considered as the main approach for the SI cancellation. It is believed that the key challenge in achieving a high level of cancellation is to overcome the nonlinear distortion in the transmit and receive chains. The majority of the nonlinearity is introduced by the power amplifier (PA), which can be dealt with by using the PA output as the reference signal for digital cancellation. Further nonlinearity comes mainly from the hydrophone pre-amplifier. For applications working in half-duplex mode, the pre-amplifier can normally be assumed to be linear due to the low received signal level. For FD operations, the strong SI might result in a nonlinear response of the pre-amplifier, and this nonlinearity should be equalized to achieve a high cancellation performance. In this paper, we propose a technique for equalizing the nonlinearity in the pre-amplifier. This is done using a basis expansion model of the nonlinear equalizer response. More specifically, the Legendre polynomials are used as the basis functions. The expansion coefficients are updated to reduce the mean squared error or a cost function derived based on the power spectrum of the received signal. The performance of the equalizer is evaluated using the experimental data with artificial nonlinear distortion and with real nonlinearity introduced by the hydrophone pre-amplifier. Both sets of results demonstrate that nonlinear distortions can be effectively equalized using the proposed adaptive equalization technique.