Decentralized link adaptation for multi-link MIMO interference system

A decentralized link adaptation algorithm designed for multi-link MIMO interference systems to jointly optimize the power and the number of links is presented in this contribution. Game theory is adapted and used for both allocating resources and admitting users (i.e. with embedded congestion control). The MIMO interference system is mapped into a multi-player game. The solution of the proposed game is provided by a new gradient based decentralized link adaptation algorithm. The new algorithm allocates adaptively the power and the modulation scheme of the transmitter and maintains the optimum number of links using soft decision criteria based on the link metric. Each link decision depends on the type of traffic and the QoS requirements. An analytical framework is provided along with simulations and an analysis of the algorithm behavior under different system conditions. This type of algorithm is applicable to spectrum sharing and power management to reduce interference and energy consumption.