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-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 time-varying frequency-selective channel proves the excellent behavior of the turbo equalizer.

This paper deals with a low complexity receiver scheme where equalization and channel decoding are jointly optimized in an iterative process. We derive the theoretical transfer function of the infinite length linear minimum mean square error (MMSE) equalizer with a priori information. A practical implementation is exposed which employs the Fast Fourier Transform (FFT) to compute the equalizer coefficients, resulting in a low complexity receiver structure. The performance of the proposed scheme is investigated for the Enhanced General Packet Radio Service (EGPRS) radio link. Simulation results show that significant power gains may be achieved with only a few (3-4) iterations. These results demonstrate that MMSE turbo equalization is an attractive candidate for singlecarrier broadband wireless transmissions in long delay-spread environments.

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 (R) and a transversal filter (T): Its major feature is the ability to deal with severe quickly timevarying 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, R comes first and whitens its own output by means of a prediction principle, while T removes the remaining intersymbol interference (ISI) thanks to the Godard (or Shalvi-Weinstein) 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.

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Underwater acoustic (UWA) sensor network deployments may be used in many applications for environmental, scientific, military and commercial purposes. Several topologies are in use, but the most widely used topology is linear. Indeed, placing nodes on a single line offers more opportunities in terms of large coverage and high-rate services.The UWA channel is a shared medium. Thus, a medium access control (MAC) protocol is necessary, primarily to regulate and coordinate nodes' access. MAC protocol design should take into consideration large propagation delays to favor better network throughput. Performance of most developed protocols in linear topologies does not exceed 1 in terms of normalized network throughput, or equivalently, channel utilization. We explore transmission schedules in three important contexts: (1) single collision domain with unicast traffic. In an N -node network, we develop transmission schedules achieving a normalized network throughput of 2 − (2/N ). This is the best that can be done in such a context, as demonstrated using a general greedy approach combined with an exhaustive search for small-size networks.(2) single collision domain with broadcast traffic. We propose a periodic per-node fair schedule with the shortest period. Achievable throughput in such conditions is close to N/2. Likewise, we prove that the throughput is upper bounded by N − 1 under the per-node fairness constraint. (3) partially-overlapping collision domains with unicast traffic. We consider a simple illustration of such a configuration. The proposed transmission schedule depicts a scenario where messages originate at one end of the network, and are sequentially relayed node-by-node (i.e., hop-by-hop) in the direction of the final destination located at the other end of the network. Furthermore, for all three discussed contexts, we build up computationally-efficient algorithms that generate transmission schedules regardless of network size. We explore the idea of exploiting non-zero propagation delays for linear topologies to improve network throughput. In recent UWA sensor networks, the linear topology is a fundamental component that may be used to build more complex network configurations. This study would then serve as a base for future research into this area.