SISO and MIMO channel estimation and symbol detection using data-dependent superimposed training

We address the problem of frequency-selective channel estimation and symbol detection using superimposed training. Both single and multiple antenna systems are studied. The superimposed training consists of the sum of a known sequence and a data-dependent sequence 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 outperform significantly existing methods based on superimposed training.