Joint scheduling and hybrid ARQ for multi-cell MU-MIMO downlink

User scheduling and multiuser multi-antenna (MU-MIMO) transmission are at the core of high-rate data-oriented downlink schemes of the next-generation of cellular systems (e.g., LTE-Advanced). Scheduling selects groups of users according to their channels vector directions and channel quality indicator (CQI). However, when scheduling is applied independently in each cell, the inter-cell interference (ICI) power at each user receiver is random and not known in advance since it changes from slot to slot depending on the scheduling decisions of all interfering base stations. In order to cope with this uncertainty, we consider the joint operation of scheduling, MU-MIMO beamforming and Automatic Repeat reQuest (ARQ). We develop a game-theoretic framework for this multi-cell decentralized scheduling problem for which we prove existence of Nash equilibria, and we build on stochastic optimization techniques in order to devise good joint scheduling and ARQ schemes. We also find “extremal” ICI power statistics that provide uniform lower and upper bounds to the values of the network utility function at all Nash equilibria of the decentralized scheduling game.