Optimizing energy for training vs. data in linearly precoded multiuser sum-rate maximization

We consider the problem of optimizing the allocation of available energy across training and data symbols under linear precoding in multiuser downlink systems with imperfect channel state information (CSI). Our figure of merit is the sum rate across all users. This paper derives a lower bound on achievable rate under linear precoding and extends existing precoder designs to the case of imperfect CSI. Optimality and separability results for the energy allocation and precoder design problems that were found previously for sum-MSE minimization are extended to the problem of sum-rate maximization when channels are modelled using uncorrelated Rayleigh block fading with equal variances of the fading coefficients. Simulation results suggest significant improvements in achievable rate under the proposed algorithm.