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In this paper we propose a blind maximum ratio combining (MRC) technique along with an initialization method to improve the performance of the blind adaptive channel shortening algorithm called multicarrier equalization by restoration of redundancy (MERRY) in the 1times2 SIMO channel context. We show through analysis and simulations that the blind MRC technique allow us to take advantage of the spatial...
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 present in the SIMO channels.
Due to its universal approximation capability, the multilayer perceptron (MLP) neural network has been applied to several function approximation and classification tasks. Despite its success in solving these problems, its training, when performed by a gradient-based method, is sometimes hindered by the existence of unsatisfactory solutions (local minima). In order to overcome this difficulty, this...
In this work, we propose an adaptive decision device based on a Kohonen network that can automatically generate the classes associated with each symbol of a 4n-QAM in the presence of non-linearities caused by the I/Q imbalance and additive Gaussian white noise, being also capable of compensating phase and gain variations produced by a time-varying flat-fading channel. Our proposal can achieve optimality...
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