Individual channel tracking and training design for one-way relay networks

In this paper, we propose a time-multiplexed-superimposed training (TMST) scheme and investigate the individual channel tracking problem in amplify-and-forward one-way relay network (OWRN) under doubly selective channel scenario. The individual channels from source to relay and from relay to destination are approximated by finite number of coefficient through the complex-exponential basis-expansion-model (CE-BEM). We develop a two-step estimator for in-BEM-CV: the standard least square (LS) estimator followed by the fast Fourier transformation (FFT) based in-BEM-CV decoupler. The training parameters are also optimized.