Weighted Sum-Rate Maximization Scheduling for MIMO Ad Hoc Networks

In this paper, we propose a duality-optimization based framework to maximize the weighted sum throughput for a multiple-input multiple-output (MIMO) ad hoc network. The new schemes include an approximate global optimization approach and an iterative search approach based on the duality framework. Transmitter adaptive precoding and receiver minimum mean-square-error (MMSE) detection for interference suppression are considered. Simulation results show that a significantly higher throughput is achieved for the dual optimization schemes than for the fixed mode precoding schemes and the transmit iterative waterfilling (IWF) scheme. The negative effects of transmit and receive antenna correlations are also studied. Results show that the proposed schemes are more robust against both transmit and receive correlations than the fixed-mode and IWF schemes.