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Robust Cognitive Beamforming With Bounded Channel Uncertainties
Department of Electrical and Electronic Engineering, University College London.
Department of Electrical and Electronic Engineering, University College London.
KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. (Signal Processing)ORCID iD: 0000-0003-2298-6774
2009 (English)In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 57, no 12, 4871-4881 p.Article in journal (Refereed) Published
Abstract [en]

This paper studies the robust beamforming design for a multi-antenna cognitive radio (CR) network, which transmits to multiple secondary users (SUs) and coexists with a primary network of multiple users. We aim to maximize the minimum of the received signal-to-interference-plus-noise ratios (SINRs) of the SUs, subject to the constraints of the total SU transmit power and the received interference power at the primary users (PUs) by optimizing the beamforming vectors at the SU transmitter based on imperfect channel state information (CSI). To model the uncertainty in CSI, we consider a bounded region for both cases of channel matrices and channel covariance matrices. As such, the optimization is done while satisfying the interference constraints for all possible CSI error realizations. We shall first derive equivalent conditions for the interference constraints and then convert the problems into the form of semi-definite programming (SDP) with the aid of rank relaxation, which leads to iterative algorithms for obtaining the robust optimal beamforming solution. Results demonstrate the achieved robustness and the performance gain over conventional approaches and that the proposed algorithms can obtain the exact robust optimal solution with high probability.

Place, publisher, year, edition, pages
2009. Vol. 57, no 12, 4871-4881 p.
Keyword [en]
Cognitive radio, interference control, MIMO, robust beamforming, radio networks, convex-optimization, power allocation, multiuser, systems
National Category
URN: urn:nbn:se:kth:diva-18973DOI: 10.1109/tsp.2009.2027462ISI: 000271958600022ScopusID: 2-s2.0-70450284436OAI: diva2:337020
QC 20100525Available from: 2010-08-05 Created: 2010-08-05 Last updated: 2012-01-13Bibliographically approved

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