This thesis investigates three possible methods to increase the performance of digital communication systems, with focus on wireless systems, by accounting for some of the channel effects that may occur. The modulation scheme plays an important role in the impact of different channel effects on system performance and this work considers both a single-carrier system and orthogonal frequency-divi...

We present a bayesian method for the blind estimation of parameters in nonlinear/nongaussian models. The studied models are called H-ARMA processes. They are generated by a memoryless polynomial transformation of an ARMA process. The nonlinearities are choosen as Her-mite polynomials. After recalling the structure of those models and their main properties that have been reported in previous pub...

The blurred image blind restoration is a difficult problem of image processing. The key is the estimation of the Point Spread Function and non-blind deconvolution algorithm. In this paper, we propose a fast robust algorithm based on radon transform-domain to determine the blur kernel function. Then the blurred images are restored by using a modified fast non-blind deconvolution method based on ...

The problem of channel estimation in code-division multiple-access systems is considered. Using only the spreading code of the user of interest, a technique is proposed to identify the impulse response of the multipath channel from the received data sequence. While existing blind methods suffer from high computational complexity (due to large SVDs) and sensitivity to accurate knowledge of the n...

This paper proposes a new blind sequence estimation method for single-input single-output (SISO) systems utilizing an optimal trellis search, which is performed by a channel-independent Viterbi algorithm (CIVA). In contrast to the traditional Viterbi algorithm that requires accurate channel estimation, CIVA does not require channel coefficients. Instead, the metrics are calculated from a bank o...

In this paper, we study an enhanced subspace based approach for the mitigation of multiple access interference (MAI) in direct-sequence code-division multiple-access (DS-CDMA) systems over frequencyselective channels. Blind multiuser detection based on signal subspace estimation is of special interest in mitigating MAI in CDMA systems since it is impractical to assume perfect knowledge of param...

Certain blind channel estimation techniques allow the identification of the channel up to a scale or phase factor. This results in singularity of the Fisher Information Matrix (FIM). The Cramér–Rao Bound, which is the inverse of the FIM, is then not defined. To regularize the estimation problem, one can impose constraints on the parameters. In general, many sets of constraints are possible but ...

In order to achieve adaptive channel coding and adaptive modulation, the main causes of degradation to system performance are the decoder selection error and modulator estimation error. The utilization of supplementary information, in an estimation system utilizing channel estimation results, blind modulation estimation, and blind encoder estimation using several decoders information and encode...

The method described here performs blind deconvolution of the beamforming output in the frequency domain. To provide accurate blind deconvolution, sparsity priors are introduced with a smoothed `1/`2 regularization term. As the mean of the noise in the power spectrum domain depends on its variance in the time domain, the proposed method includes a variance estimation step, which allows more rob...