Time-varying channel estimation and symbol detection for OFDM systems using superimposed training

The problem of superimposed training (ST) based time-varying channel estimation and symbol detection for the OFDM system is addressed. Unlike the conventional approach, the effects of the unknown data on channel estimation are fully cancelled. The performance of the proposed approach is shown to significantly outperform existing methods based on ST.