A joint adaptive beamforming and user scheduling algorithm for downlink network MIMO systems

In this paper, we study multiple-input single-output downlink cellular systems which jointly design adaptive inter-cell interference cancellation and user scheduling assuming that partial channel state information (CSI) is shared among base stations (BSs). Since the optimal solution requires high complexity, we propose a new low complexity algorithm which selects the best users and their beamforming (BF) strategies in terms of maximizing the weighted sum rate. To this end, we first develop a simple threshold criterion for each user to decide the preferred BF strategy based on the derivation of the expected signal-to-interference-plus-noise ratio. Then, according to users' feedback about their decisions, a successive user and BF selection algorithm is performed at the BSs. From simulation results, we show that combined with proportional fair scheduling, the proposed scheme provides excellent sum rate performance with very low computational complexity.