Direct FIR Linear Equalization of Doubly Selective Channels Based on Superimposed Training

Design of doubly-selective linear equalizers for single user frequency-selective time-varying communications channels is considered using superimposed training and without first estimating the underlying channel response. Both the time-varying channel as well as the linear equalizers are assumed to be described by a complex exponential basis expansion model (CE-BEM). A periodic (non-random) training sequence is arithmetically added (superimposed) at a low power to the information sequence at the transmitter before modulation and transmission. There is no loss in information rate. Knowledge of the superimposed training is exploited to design the FIR linear equalizer. An illustrative simulation example is presented.