Iterative robust downlink beamforming in cognitive radio networks

The problem of multi-user worst-case robust downlink beamforming and power allocation in a cognitive radio (CR) framework is studied. The goal is to minimize the total transmitted power while providing the secondary users (SUs) with a minimum acceptable quality-of-service (QoS), with additional constraints on the total interference leaked to the primary network (PN). An iterative algorithm has been proposed to solve this problem. In each iteration the algorithm approximates the worst-case covariance mismatch from the solution of the previous iteration und performs a fixed-point iteration that is based on uplink-downlink duality. Computer simulations show that the proposed technique converges to the global optimal solution at reduced computational complexity compared to the existing methods that rely on convex optimization.