5th International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications

Research Article

SINR balancing in the downlink of cognitive radio networks with imperfect channel knowledge

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  • @INPROCEEDINGS{10.4108/ICST.CROWNCOM2010.9199,
        author={Muhammad Fainan Hanif and Peter J. Smith and Mohamed-Slim Alouini},
        title={SINR balancing in the downlink of cognitive radio networks with imperfect channel knowledge},
        proceedings={5th International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications},
        publisher={IEEE},
        proceedings_a={CROWNCOM},
        year={2010},
        month={9},
        keywords={Array signal processing Channel estimation Chromium Downlink Interference Signal to noise ratio Uncertainty},
        doi={10.4108/ICST.CROWNCOM2010.9199}
    }
    
  • Muhammad Fainan Hanif
    Peter J. Smith
    Mohamed-Slim Alouini
    Year: 2010
    SINR balancing in the downlink of cognitive radio networks with imperfect channel knowledge
    CROWNCOM
    IEEE
    DOI: 10.4108/ICST.CROWNCOM2010.9199
Muhammad Fainan Hanif1,*, Peter J. Smith1,*, Mohamed-Slim Alouini2,*
  • 1: Department of Electrical and Computer Engineering, University of Canterbury, Christchurch, New Zealand
  • 2: Electrical Engineering Program, KAUST, Thuwal, Saudi Arabia
*Contact email: mfh21@uclive.ac.nz, p.smith@elec.canterbury.ac.nz, slim.alouini@kaust.edu.sa

Abstract

In this paper we consider the problem of signal-to-interference-plus-noise ratio (SINR) balancing in the downlink of cognitive radio (CR) networks while simultaneously keeping interference levels at primary user (PU) receivers (RXs) below an acceptable threshold with uncertain channel state information available at the CR base-station (BS). We optimize the beam-forming vectors at the CR BS so that the worst user SINR is maximized and transmit power constraints at the CR BS and interference constraints at the PU RXs are satisfied. With uncertainties in the channel bounded by a Euclidean ball, the semidefinite program (SDP) modeling the balancing problem is solved using the recently developed convex iteration technique without relaxing the rank constraints. Numerical simulations are conducted to show the effectiveness of the proposed technique in comparison to known approximations.