Adaptive Beam Selection Techniques for Opportunistic Beamforming

In multi-antenna downlink systems the optimization of linear preceding is severely hampered by the amount of feedback. An efficient solution consists in opportunistic schemes, which generate M random beams and schedule the users with the highest signal-to-noise-plus-interference ratios (SINRs), which can be made available to the transmitter with very little feedback. Although this technique has been shown to be optimal for asymptotically large number of users, severe performance degradation occurs in practical system where the number of users is limited. In this paper we propose an enhancement of this strategy based on an adaptive beam selection procedure. Instead of transmitting all the generated beams, the scheduler picks the optimum subset of beams that maximizes the system sum-rate according to the feedback information. We propose and compare several beam selection algorithms according to different complexity requirements. In particular, we show that the proposed approaches give substantial gains with respect to conventional opportunistic schemes