Convex optimization-based beamforming in cognitive radio multicast transmission
A novel algorithm for transmit beamforming to single cochannel multicast group is presented in this paper. We consider the max-min fairness (MMF) based beamforming problem where the maximization of the smallest receiver signal-to-noise ratio (SNR) over the secondary users subject to constraints on the transmit power and interference caused to the primary users. It is shown that this problem, which is nonconvex NP-hard, can be approximated by a convex second-order cone programming (SOCP) problem. Then, an iterative algorithm which successively improves the SOCP approximation is presented. Simulation results show the superior performance of the proposed approach, together with a reduced computational complexity, as compared to the state-of-the-art approach.