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TitleStatistically robust cognitive radio beamforming
Publication TypeConference Paper
Year of Publication2013
AuthorsSingh, S., Teal P.D., Dmochowski P.A., and Coulson A.J.
Conference Name2013 Australian Communications Theory Workshop, AusCTW 2013
Date Published2013
KeywordsAdditive Gaussian noise, Beamforming, Channel state information, Cognitive radio, Cognitive radio network, Convex programming, Cumulative distribution function, Gaussian noise (electronic), Optimisation problems, Optimization, Outage probability constraints, Outages, Partial channel state information, Semi-definite program (SDP), Signal interference, Signal to noise ratio, Signalto-interference- and-noise ratios (SINR), Transmitters
AbstractWe consider a cognitive radio (CR) network consisting of a secondary user transmitter (SU-Tx) equipped with multiple antennas and a secondary user receiver (SU-Rx) that share spectrum with multiple primary user transmitter (PU-Tx) and receiver (PU-Rx) pairs. We assume that the CR has a loose cooperation with the primary network and therefore, only partial channel state information of each of the PU-Tx to PU-Rx and SU-Tx to each PU-Rx links is available. Furthermore, we assume that the SU-Tx to SU-Rx link CSI is imperfect, with the channel error modelled as additive Gaussian noise. Under these assumptions, we propose a new statistically robust CR beamformer where the total SU-Tx transmit power is minimised subject to PU-Rx and SU-Rx outage probability constraints. We present expressions for PU-Rx and SU-Rx outage probabilities and formulate the robust beamformer optimisation problem as a convex semidefinite program (SDP). SU-Tx transmit power, PU-Rx signal-to-interference- and-noise ratio (SINR) and SU-Rx signal-to-noise (SNR) cumulative distribution functions (CDFs) are obtained through solution of our optimisation problem. © 2013 IEEE.

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