Optimal Precoder Design Maximizing the Worst-Case Average Received SNR for Massive Distributed MIMO Systems

In this letter, we consider a distributed multiple-input multiple-output (D-MIMO) system, where the channel is flat fading and may be correlated, and experiences both small and large-scale fading. We assume that the full knowledge of channel state information (CSI) is available at the receiver and only the first-and second-order statistics of the channel are available at the transmitter. For such a system employing the linear zero-forcing (ZF) receiver, an efficient linear precoding technique is proposed to optimize the worst-case performance of average signal-to-noise ratio (SNR) at the receiver and a simple closed-form optimal precoder is derived. In addition, under some realistic assumptions, some significant asymptotic properties are established for the massive D-MIMO system designed in this letter. Computer simulations verify our theoretic analysis and show that our presented optimal system attains significant performance gains over the currently available equal power-loading system.