Robust beamforming in cognitive radio

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 th...

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Published inIEEE 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
LanguageEnglish
Published New York, NY IEEE 01.02.2010
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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Abstract 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.
AbstractList 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 worstcase based systems.
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.
Author Kai-kit Wong
Tung-Sang Ng
Shaodan Ma
Gan Zheng
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Issue 2
Keywords 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
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Snippet 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...
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SubjectTerms 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)
Title Robust beamforming in cognitive radio
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