Joint Beamforming and Antenna Selection for Sum Rate Maximization in Cognitive Radio Networks

This letter studies joint transmit beamforming and antenna selection at a secondary base station (BS) with multiple primary users (PUs) in an underlay cognitive radio multiple-input single-output broadcast channel. The objective is to maximize the sum rate subject to the secondary BS transmit power,...

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Bibliographic Details
Published inIEEE communications letters Vol. 21; no. 6; pp. 1369 - 1372
Main Authors Van-Dinh Nguyen, Nguyen, Chuyen T., Nguyen, Hieu V., Oh-Soon Shin
Format Journal Article
LanguageEnglish
Published New York IEEE 01.06.2017
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Algorithms
Antenna selection
Antennas
Approximation
Array signal processing
Beamforming
Broadcasting
Cognitive radio
Computer simulation
Construction methods
Interference
Iterative methods
Lead
Mathematical analysis
Maximization
Networks
nonconvex programming
Optimization
sum rate
transmit beamforming
Transmitting antennas
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ISSN1089-7798
1558-2558
DOI10.1109/LCOMM.2017.2679186

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Summary:This letter studies joint transmit beamforming and antenna selection at a secondary base station (BS) with multiple primary users (PUs) in an underlay cognitive radio multiple-input single-output broadcast channel. The objective is to maximize the sum rate subject to the secondary BS transmit power, minimum required rates for secondary users, and PUs' interference power constraints. The utility function of interest is nonconcave and the involved constraints are nonconvex, so this problem is hard to solve. Nevertheless, we propose a new iterative algorithm that finds local optima at the least. We use an inner approximation method to construct and solve a simple convex quadratic program of moderate dimension at each iteration of the proposed algorithm. Simulation results indicate that the proposed algorithm converges quickly and outperforms existing approaches.
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ISSN:1089-7798
1558-2558
DOI:10.1109/LCOMM.2017.2679186