Abstract
This paper considers an underlay cognitive radio network where primary and secondary networks coexist. The optimization target is to minimize the sum power of secondary transmitters while satisfying the worst case minimum SINR constraint for each secondary user (SU) and maximum aggregate interference constraint for each primary user (PU). Imperfect channel state information (CSI) is assumed, and the corresponding CSI errors are bounded by ellipsoids. We propose an alternating direction method of multipliers-based decentralized beamforming algorithm which relies only on local imperfect CSI and limited backhaul signaling. The convergence behavior of the proposed algorithm is studied via numerical examples.
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