Channel estimation and symbol detection for block transmission using data-dependent superimposed training
Mounir Ghogho, Des McLernon, Enrique Alameda-Hernandez, Ananthram Swami · IEEE Signal Processing Letters · 2005
We address the problem of frequency-selective channel estimation and symbol detection using superimposed training. The superimposed training consists of the sum of a known sequence and a data-dependent sequence that is unknown to the receiver. The data-dependent sequence cancels the effects of the unknown data on channel estimation. The performance of the proposed approach is shown to significantly outperform existing methods based on superimposed training (ST).