Optimized signaling for MIMO interference systems with feedback

The system mutual information of a multiple-input multiple-output (MIMO) system with multiple users which mutually interfere is considered. Perfect channel state information is assumed to be known to both transmitters and receivers. Asymptotic performance analysis shows that the system mutual information changes behavior as the interference becomes sufficiently strong. In particular, beamforming is the optimum signaling for all users when the interference is large. We propose several numerical approaches to decide the covariance matrices of the transmitted signals and compare their performance in terms of the system mutual information. We model the system as a noncooperative game and perform iterative water-filling to find the Nash equilibrium distributively. A centralized global approach and a distributed iterative approach based on the gradient projection method are also proposed. Numerical results show that all proposed approaches give better performance than the standard signaling, which is optimum for the case without interference. Both the global and the iterative gradient projection methods are shown to outperform the Nash equilibrium significantly.

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