MIMO downlink scheduling with non-perfect channel state knowledge

Downlink scheduling schemes are well-known and widely investigated. In the multiuser MIMO (broadcast) case, downlink scheduling in the presence of non-perfect CSI is only scantly treated. In this paper we provide a general framework within which the problem can be addressed systematically. Then, we focus on the special case of proportional fairness and ¿hard fairness¿, with Gaussian coding and linear beamforming. We find that the naive scheduler that ignores the quality of the channel state information may be very suboptimal. We propose novel simple schemes that perform very well in practice. Also, we illuminate the key role played by the channel state prediction error: our schemes treat in a fundamentally different way users with ¿predictable¿ or ¿non-predictable¿ channels, and allocate these classes of users over time in a near-optimal fashion.