Robust beamforming in cognitive radio

• Published in: IEEE transactions on wireless communications Vol. 9; no. 2; pp. 570 - 576
• Main Authors: Zheng, Gan, Ma, Shaodan, Wong, Kai-kit, Ng, Tung-Sang
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.02.2010; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Antennas; Applied sciences; Array signal processing; Beamforming; Channel state information; Channels; Chromium; Closed-form solution; Cognitive radio; Detection, estimation, filtering, equalization, prediction; Exact sciences and technology; Exact solutions; Gaussian noise; Information, signal and communications theory; Interference constraints; interference control; Iterative algorithms; Mathematical models; Networks; Noise robustness; Optimization; Radio; Radio transmitters; Radiocommunication specific techniques; Radiocommunications; robust beamforming; Signal and communications theory; Signal, noise; Studies; Systems, networks and services of telecommunications; Telecommunications; Telecommunications and information theory; Transmission and modulation (techniques and equipments); Performance evaluation; Parameter estimation; robust beamforming; Worst case method; Transmitter; Iterative method; Cognitive radio; Algorithm; Beam forming; Optimization; interference control; Gaussian noise; Channel estimation; Optimal solution; Numerical simulation; Radio communication; Antenna; Software radio
• ISSN: 1536-1276; 1558-2248
• DOI: 10.1109/TWC.2010.5403537

This letter considers the multi-antenna cognitive radio (CR) network, which has a single secondary user (SU) and coexists with a primary network of multiple users. Our objective is to maximize the service probability of the SU, subject to the interference constraints on the primary users (PUs) in the form of probability. Exploiting imperfect channel state information (CSI), with its error modeled by added Gaussian noise, we address the optimization for the beamforming weights at the secondary transmitter. In particular, this letter devises an iterative algorithm that can efficiently obtain the robust optimal beamforming solution. For the case with one PU, we show that a much simpler algorithm based on a closed-form solution for the antenna weights of a given power can be presented. Numerical results reveal that the optimal solution for the constructed problem provides an effective means to tradeoff the performance between the PUs and the SU, bridging the non-robust and worst-case based systems.