Optimization of an Amplify-and-Forward Relay Network Considering Time Delay and Estimation Error in Channel State Information

This paper presents the optimization of an amplify-and-forward (AF) relay network with time delay and estimation error in channel state information (CSI). The CSI time delay and estimation error are modeled by the channel time variation model and stochastic error model, respectively. The conditional probability density function of the ideal CSI upon the estimated CSI is computed based on these two models, and it is used to derive the conditional expectation of the mean square error (MSE) between estimated and desired signals upon estimated CSI, which is minimized to optimize the beamforming and equalization coefficients. Computer simulations show that the proposed method obtains lower bit error rate (BER) than the conventional minimum MSE and the maxmin SNR strategies when CSI contains time delay and estimation error.