On Channel Estimation and Capacity for Amplify and Forward Relay Networks

Relay networks have received considerable attention recently, especially when limited size and power resources impose constraints on the number of antennas within a wireless sensor network. In this paper, we design and analyze a training based linear mean square error (LMMSE) channel estimator for time division multiplex amplify-and-forward (AF) relay networks. For the purpose of performance comparison we consider three distinct cases; In the first scenario, each relay estimates its backward and forward channels, in the second scenario each relay knows its backward and forward channels perfectly and finally in the third scenario relays have no knowledge of channels. Finally, we find a lower bound for the capacity considering the effect of training and estimation error.