In this paper, we design a segment training based individual channel estimation (STICE)
scheme in the classical three-node it amplify-and-forward (AF) one-way relay network
(OWRN). The linear minimum mean-square-error (LMMSE) channel estimator is used to
obtain a good initialization, and an iterative maximum a posteriori (MAP) channel estimator
is developed to improve the estimation accuracy. We then investigate the underlying power
allocation at the relay node both to minimize the mean-square-error (MSE) of the individual�…

In this paper, we design a segment training based individual channel estimation scheme in
the classical three-node amplify-and-forward one-way relay network (OWRN). We
investigate the underlying power allocation at the relay to minimize the mean-square-error
(MSE) of the individual channel estimation and to maximize the average effective signal-to-
noise ratio (AESNR) of the data detection. The optimal/sub-optimal power allocation
schemes are also derived for the two objectives. Extensive numerical results are provided to�…