SINR-interference tradeoff beamforming for MISO cognitive radio network

This paper considers the spectrum sharing multiple-input single-output (MISO) underlay cognitive radio network, in which multiple primary users (PUs) coexist with multiple secondary users (SUs). A weighted trade-off beamforming is designed to balance the minimum signal-to-interference-plus-noise ratio (SINR) of the SUs and the maximum interferences to the PUs under a limited transmit power constraint. When the perfect channel state information at transmitter (CSIT) is available, the multi-objective function is converted into an auxiliary parametric single-objective problem. The underlying problem is solved by using semidefinite programming (SDP) relaxation. Due to the inevitable CSIT errors, a robust design is developed to provide robustness against the worst-case errors. Simulation results show that the proposed weighted trade-off design has the ability to achieve the Pareto optimal points