Evolutionary channel state information feedback control for interference alignment

Interference alignment (IA) has been well recognized as a promising technique to obtain a large multiplexing gain in multiple input multiple output (MIMO) interference channels. However, most of the existing IA schemes require global channel state information (CSI) at the transmitter to design precoding vectors, which causes a large amount of feedback bits. To reduce the feedback overhead, in this paper, we model the evolution and dynamic behavior of the CSI feedback rate control problem using the evolutionary game theory over orthogonal feedback channels with a total bandwidth constraint. The game utility is defined as the performance gain by CSI feedback minus the price as a linear function of the CSI feedback rate, subject to an overall bandwidth constraint. Then, an algorithm for the implementation of the evolution process is also presented. The proposed game-theoretic framework for modeling the interactions among the feedback of multiple users can be used to efficiently control the CSI feedback amount while achieving fairness among all the mobile receivers.