A System on a Programmable Chip Architecture for Data-Dependent Superimposed Training Channel Estimation

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Executive Summary

Channel estimation in wireless communication systems is usually accomplished by inserting, along with the information, a series of known symbols, whose analysis is used to define the parameters of the filters that remove the distortion of the data. Nevertheless, a part of the available bandwidth has to be destined to these symbols. Until now, no alternative solution has demonstrated to be fully satisfying for commercial use, but one technique that looks promising is Superimposed Training (ST).

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