Bandwidth Efficient Pilot Assisted Transmission Over Double-Selective Wireless Fading Channels Using Superimposed Training

摘要

We propose to estimate time-varying frequency-selective channels using data-dependent super-imposed training (DDST) and a basis expansion model (BEM). The superimposed training consists of the sum of a known sequence and a data-dependent sequence, which is unknown to the receiver. The data-dependent sequence cancels the effects of the unknown data on channel estimation. Symbol detection is performed using MMSE equalization. The method is compared to time- division-multiplexing-based methods.