Underwater acoustic communication current needs are increasing. Civil and military applications are large. In this context, GESMA (Groupe d'Etudes Sous-Marines de l'Atlantique), initiated the Project TRIDENT (TRansmission d'Images et de Donnees EN Temps reel). Project objective is to develop a high data rate link allowing the transmission of various information (text, images...). A real-time receiver platform, using a Digital Signal Processor (DSP) and based on a spatio-temporal equalizer developed and patented by ENST Bretagne, was carried out to reduce the various perturbations brought by the underwater acoustic channel (UWA). Sea trials, realized in 2002 and 2003, permitted to validate the receiver platform. The different results show the robustness of the TRIDENT system for transmission in a strongly disturbed channel. The TRIDENT system allows data transmissions with a bit data rate ranging from 8 to 25 kbps for distances higher than 2000 meters.

This paper deals with a receiver scheme where adaptive equalization and channel decoding are jointly optimized in an iterative process. This receiver scheme is well suited for transmissions over a frequency-selective channel with large delay spread and for high spectral efficiency modulations. A low-complexity soft-input soft-output M-ary channel decoder is proposed. Turbo equalization allows intersymbol interference to be reduced drastically. For most time-invariant discrete channels, the turbo-equalizer performance is close to the coded Gaussian channel performance, even for low signal-to-noise ratios. Finally, results over a time-varying frequency-selective channel proves the excellent behavior of the turbo equalizer.

This paper introduces a novel blind adaptive multiple-input decision-feedback equalizer (MI-DFE) which is basically characterized by its ability to self-optimize its configuration, in terms of both structure and criteria, according to the severity of the transmission medium. In the first running mode, the novel equalizer is recursive, linear and "blindly" adapted by criteria leading to a solution closely related to the minimum MSE solution. In the second running mode, it becomes the conventional MI-DFE. From the viewpoints of both robustness and spectral efficiency, this equalizer proves to be very attractive since it avoids pathological behaviors, often encountered with the conventional trained MI-DFE, while requiring no training sequence. Furthermore, its very high speed of convergence renders it competitive in various standard applications, even in the case of burst mode transmission systems. Finally, the novel blind MI-DFE has been successfully tested on underwater acoustic communications signals, in a very severe context. The results are clearly convincing.

This paper presents a novel unsupervised (blind) adaptive decision feedback equalizer (DFE). It can be thought of as the cascade of four devices, whose main components are a purely recursive filter (/spl Rscr/) and a transversal filter (/spl Tscr/). Its major feature is the ability to deal with severe quickly time-varying channels, unlike the conventional adaptive DFE. This result is obtained by allowing the new equalizer to modify, in a reversible way, both its structure and its adaptation according to some measure of performance such as the mean-square error (MSE). In the starting mode, /spl Rscr/ comes first and whitens its own output by means of a prediction principle, while /spl Tscr/ removes the remaining intersymbol interference (ISI) thanks to the Godard (1980) (or Shalvi-Weinstein (1990)) algorithm. In the tracking mode the equalizer becomes the classical DFE controlled by the decision-directed (DD) least-mean-square (LMS) algorithm. With the same computational complexity, the new unsupervised equalizer exhibits the same convergence speed, steady-state MSE, and bit-error rate (BER) as the trained conventional DFE, but it requires no training. It has been implemented on a digital signal processor (DSP) and tested on underwater communications signals-its performances are really convincing.

This paper presents convincing results obtained with the self-adaptive decision feedback equalizer (SADFE) previously described by Labat et al. (1996). This equalizer is successfully applied to 64 and 256-QAM signals transmitted over channels corrupted by severe intersymbol interference (ISI) with specific examples concerning the digital television transmission. It clearly appears that with the same computational complexity, this new blind decision feedback equalizer that can be used when no training sequence is available exhibits nearly the same performance as the classical trained DFE in terms of convergence speed, residual mean-square error (MSE) and bit error rate (BER).