Channel Estimation for Full-Duplex Relay Transmission in Cloud Radio Access Networks

Relay in full-duplex (FD) mode can achieve higher spectrum efficiency than that in half-duplex mode, while it is crucial to suppress relay self-interference to ensure transmission quality which requires instantaneous channel state information (CSI). In this paper, the channel estimation issue in FD amplify-and-forward relay networks is considered, where the training-based estimation technique is adopted. Firstly, the least square (LS) estimation is implemented to obtain composite channel coefficients of source-relay-destination (SRD) channel and relay loop-interference (LI) channel in order to assist destination in performing data detection. Secondly, both LS and maximum likelihood estimation methods are utilized to perform individual channel estimation aiming at supporting successive interference cancelation at destination. Finally, simulation results demonstrate the effectiveness of both composite and individual channel estimation, and the presented ML method can achieve lower MSEs than LS solution.