Cramér-Rao bound for channel estimation in amplify-and-forward relaying networks

In this paper, we consider a three-node amplify-and-forward (AF) relaying network, consisting of a source S, a destination D and a half-duplex relay node R, where only D is equipped with channel estimator. For a block flat fading channel model, we derive the Bayesian Cramér-Rao lower bound (CRLB) and the mean-squared error (MSE) of the linear minimum mean square error (LMMSE) channel estimate. For a fixed transmission block length and a total transmit power constraint, we investigate the optimal power allotment between S and R, such that Bayesian CRLB and the MSE of the LMMSE channel estimate are minimized.