  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.
