MIMO Gaussian channels with arbitrary inputs: optimal precoding and power allocation

We investigate the linear precoding and power allocation policies that maximize the mutual information for general multiple-input multiple-output (MIMO) Gaussian channels with arbitrary input distributions, by capitalizing on the relationship between mutual information and minimum mean-square error. The optimal linear precoder satisfies a fixed-point equation as a function of the channel and the input constellation. For nonGaussian inputs, a nondiagonal precoding matrix in general increases the information transmission rate, even for parallel noninteracting channels. Whenever precoding is precluded, the optimal power allocation policy also satisfies a fixed-point equation; we put forth a generalization of the mercury/waterfilling algorithm, previously proposed for parallel noninterfering channels, in which the mercury level accounts not only for the nonGaussian input distributions, but also for the interference among inputs.

• Type: Journal
• Year: 2010
• Where: TIT
• Authors: Fernando Pérez-Cruz, Miguel R. D. Rodrigues, Sergio Verdú
• Keywords: Education, Fixed-point Equation, Input Distributions, Power Allocation, TIT 2010