We derive a lower bound on the capacity of discrete-time Rician-fading channels that are selective both in time and frequency. The noncoherent setting is considered, where neither the transmitter nor the receiver knows a priori the actual channel realization. Single-input single-output communications subject to both average and peak power constraints are investigated. The lower bound assumes independent and identically distributed input data and is expressed as a difference between two terms. The first term is the information rate of the coherent channel with a weighted signal-to-noise ratio that results from the peak-power limitation. The second term is a penalty term, explicit in the Doppler spectrum of the channel, that captures the effect of the channel uncertainty induced by the noncoherent setting. The impact of channel selectivity and power constraints are discussed, and numerical applications on an experimental Rician channel surveyed in an underwater acoustic environment are also provided.

In order to provide a concise time-varying SISO channel model, the principle of maximum entropy is applied to scattering function derivation. The resulting model is driven by few parameters that are expressed as moments such as the channel average power or the Doppler spread. Physical interpretations of the model outputs are discussed. In particular, it is shown that common Doppler spectra such as the flat or the Jakes spectrum fit well into the maximum entropy framework. The Matlab code corresponding to the proposed model is available at http://perso.telecom-bretagne.eu/fxsocheleau/software.

In this paper, performance comparison of frequency-domain (FD) minimum mean square error (MMSE) turbo equalization for OFDM and single-carrier (SC) transmission in ST-BICM systems is investigated. In particular, we propose a joint formulation of the frequency- domain OFDM and SC MMSE turbo equalizer which enable to bring out similarities and differences between the two transmission schemes. This provides a new view on the topic. The relevance of the proposed approach is confirmed by comparing the lower bound of the iterative equalizing process with the corresponding analytical results. Simulation results over multipath Rayleigh block fading channels for various MIMO configurations show the benefits provided by each scheme.

In the above titled paper (ibid., vol. 19, no. 9, pp. 1744-1752, Sep 01), equation (33) contained an error. The correct equation is presented here.

This paper presents a simple approach to assess performance that can be achieved by the MMSE turbo equalizer in ST-BICM systems over multipaths Rayleigh block fading channels with i.i.d fading statistics. By considering perfect information exchange between the SISO decoder and the linear MMSE equalizer, the performance reaches the matched filter bound, and a closed form expression of the corresponding probability of bit error can be derived at the output of the equalizer. In particular, we emphasize that the suggested approach provides an attractive and reliable tool for performance validation consistently with the proposed expression of the probability of bit error. Simulations for 4-PSK and 8-PSK modulated signals show the relevance of the proposed approach and the full benefit provided by the MMSE turbo equalizer. In addition some clarification of the signal-to- noise ratio definition is pointed out.

In this paper, a closed-form solution minimizing the Godard or constant modulus (CM) cost function under the practical conditions of finite SNR and finite equalizer length is derived. While previous work has been reported by Zeng et al., IEEE Trans. Information Theory, 1998, to establish the link between the constant modulus and Wiener receivers, we show that under the Gaussian approximation of intersymbol interference at the output of the equalizer, the CM finite-length receiver is equivalent to the nonblind MMSE equalizer up to a complex gain factor. Some simulation results are provided to support the Gaussian approximation assumption

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 single-carrier broadband wireless transmissions in long delay-spread environments.

We describe the implementation of a low-complexity minimum mean-square error (MMSE) turbo-equalizer on the Texas Instruments (TI) TMS320VC5509 device, a low-cost 16-bit fixed-point DSP typically designed for mobile terminals. A data rate of 207 Kb/s per iteration has been achieved. With carefully optimized data quantization, the resulting fixed-point receiver exhibits virtually no performance degradation with respect to an ideal (unquantized) floating-point turbo-equalizer.

This work deals with a receiver for the DS-CDMA downlink. User signals are transmitted synchronously using orthogonal spreading codes. Multipath propagation of the transmission channel generates inter-chip interference which deteriorates performance. Linear chip-level equalization followed by a filter matched to the code of the desired user allows performance to be improved. We show that an infinite-length implementation of the linear MMSE chip-level equalizer can be achieved using two recursive filters optimized from a blind criterion. Simulation results over a multipath Rayleigh channel show that the proposed receiver outperforms the finite-length implementation of the linear MMSE receiver and the ideal RAKE receiver.

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.