Design of training sequences and channel estimation for amplify-and-forward two-path relaying networks

This paper proposes a new channel estimation scheme for two-path relaying networks where two amplify-and-forward (AF) half-duplex relay nodes alternatively transmit the signals received from a source node. The channel estimation and interference cancellation would be mutually conditional in two-path relaying networks. To overcome such a difficulty, we design new training sequences and propose precoding matrices for use at the source and relays. Deriving the Cramer-Rao lower bound (CRLB), it is shown that the proposed estimator is efficient, i.e., the proposed channel estimation scheme achieves the CRLB. The performance of the proposed channel estimation is evaluated through the computer simulations where the validity of the theoretical analysis is also demonstrated.