Abstract
Beamforming for multi-input multi-output (MIMO) cognitive networks is considered in the presence of channel uncertainty induced by errors in estimating cognitive-to-primary channels. A robust beamforming problem is formulated to optimize an appropriate cognitive radio network-wide performance metric, while enforcing protection of the primary system. In spite of the non-convexity of the resultant optimization problem, a block coordinate ascent algorithm is developed with provable convergence to a stationary point. Enticingly, the novel scheme also lends itself naturally to a distributed implementation. Numerical results are reported to corroborate the analytical findings.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
