Downlink transceiver beamforming and admission control for massive MIMO cognitive radio networks

In this paper, an optimization framework is proposed for joint transceiver beamforming and admission control in massive MIMO cognitive radio networks. The objective of the optimization problem is to support maximum number of secondary users in downlink transmission with constraints on the total power allocated to users, the rate achieved at secondary users and the interference at the primary nodes. The proposed framework takes into account the imperfect knowledge of the channels between the secondary and the primary nodes and also mitigates the interference caused by the primary users at secondary receivers. In order to solve the underlying NP-hard problem, we propose a three-step algorithm with two alternative schemes for power allocation, namely: equal power and equal rate. In addition, we provide a solution by reducing the problem to an Integer Linear Program (ILP). The performances of equal rate, equal power, and ILP methods are studied in under different constraints.