Cristiano Magalhães Panazio

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— In this paper, we make use of a blind adaptive linear predictor for channel shortening in single input multiple output (SIMO) channels. We compare our approach to the so-called MERRY blind channel shortener. We assess through simulations that our proposed approach provides faster convergence rate and it better exploits the spatio-temporal diversity(More)
We propose a new timing error detector for timing tracking loops inside the Rake receiver in spread spectrum systems. Based on a particle filter, this timing error detector jointly tracks the delays of each path of the frequency-selective channels. Instead of using a conventional channel estimator, we have introduced a joint time delay and channel estimator(More)
In this paper, we propose a pilot-symbol-aided iterative channel estimation for coded OFDM-based systems. We use the symbol APP provided by the channel decoder to form groups of virtual pilots. According to their reliabilities, we combine these groups to improve the channel estimation. We also compare the proposed algorithm with the EM algorithm.
The performance of three downlink beamforming techniques in a TDMA/FDD context is investigated in the present work. Two techniques based on the uplink processing are studied together with a decoupled space-time structure that provides the antenna weights. The third one is a downlink beamforming technique, based on the spatial covariance matrix, which is(More)
This paper shows how performance gain in a mobile radio environment can be achieved by using joint space-time equalization and decoding. We apply different joint procedures with two types of space-time equalization techniques. As a matter of fact, the joint techniques are able to provide a considerable gain with none to small additional computational cost.(More)
pour l'obtention du doctorat spécialité : lasers, métrologie, communications par Cristiano PANAZIO sujet : ´ Etude fréquentielle de l'´ etalement de spectre et impact sur la conception d'un récepteur de radiocommunications universel Soutenue le 24/05/2005 devant le jury composé de Abstract The frequency domain processing provides an unified analysis for the(More)
This paper shows that it is possible to achieve convergence to the optimum solution in a blind equalization framework with the use of least mean square algorithm in decision-directed mode (DD-LMS). In linear equalizers structures, the attainment of the optimum solution strongly depends on the filter weights initialization. We also show that(More)
In this work we present a new paradigm for unsuper-vised nonlinear equalization based on prediction-error fuzzy filters. Tests i n different linear channel scenarios are carried out i n order t o assess the performance of t h e equalizer. T h e results show that the proposal is solid and may provide a performance close to that of a Bayesian equalizer. The(More)
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