Consider a MIMO multi-cellular network (also known as an interfering broadcast channel) where each base station transmits signals to the users in its own cell. The basic problem is to design linear transmit/receive beamformers and schedule users across a fixed set of time slots so as to maximize the system throughput in the presence of both inter and intra cell interference. In this paper, we propose a joint linear transceiver design and user grouping scheme for sum utility maximization that is based on iterative minimization of weighted mean squared error (MSE). The proposed algorithm only needs local channel knowledge and its convergence to a stationary point is guaranteed for some well-known utility functions, while ensuring user fairness. The simulation results show that the proposed formulation/algorithm can offer significantly higher system throughput than the standard multi-user MIMO techniques such as the SVD-MMSE strategy, while maintaining user fairness. Furthermore, the proposed algorithm exhibits fast convergence and is amenable to distributed implementation with limited information exchange.
- Multi-user channel
- User scheduling