Simultaneous Estimation of Multi-Relay MIMO Channels

Abstract—This paper addresses training-based channel estima-tion in distributed amplify-and-forward (AF) multi-input multi-output (MIMO) multi-relay networks. To reduce channel estimation over-head and delay, a training algorithm that allows for simultaneous estimation of the entire MIMO cooperative network’s channel parameters at the destination node is proposed. The exact Cramér-Rao lower bound (CRLB) for the problem is presented in closed-form. Channel estimators that are capable of estimating the overall source-relay-destination channel parameters at the destination are also derived. Numerical results show that while reducing delay, the proposed channel estimators are close to the derived CRLB over a wide range of signal-to-noise ratio values and outperform existing channel estimation methods. Finally, extensive simulations demonstrate that the proposed training method and channel esti-mators can be effectively deployed in combination with cooperative optimization algorithms to significantly enhance the performance of AF relaying MIMO systems in terms of average-bit-error-rate. I