Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Precoding and Signal Shaping for Digital Transmission
Precoding and Signal Shaping for Digital Transmission
Handbook of Blind Source Separation: Independent Component Analysis and Applications
Handbook of Blind Source Separation: Independent Component Analysis and Applications
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We propose combining supervised and unsupervised algorithms in order to improve the performance of multiple-input multiple output digital communication systems which make use of decision-feedback equalizers at the receiver. The basic idea is to avoid the periodical transmission of pilot symbols by using a simple criterion to determine the time instants when the performance obtained with an unsupervised algorithmis poor or, equivalently, those instants when pilot symbols must be transmitted. Simulation results show how the novel approach provides an adequate BER with a low overhead produced by the transmission of pilot symbols.