认知无线电网络中的动态波束形成

doi:10.3969/j.issn.0255-8297.2015.03.001

Abstract

Abstract: Cognitive radio network has the potential of enhancing spectrum utilization.An effective beamforming algorithm can protect primary user from excessive interference while ensuring a meaningful QoS to the secondary system. Conventional beamforming algorithms focus on stationary targets, whereas the cognitive radio nodes are mobile. Dynamic beamforming is investigated in this paper. The direction of arrival (DOA) of a moving target is tracked by a particle filter algorithm. The derived DOA estimation is then used to model the channel between the base station and the users. Three different beamforming
schemes are proposed aiming at maximizing signal-to-noise ratio (SNR), minimizing inference, and SNR balancing, respectively. SNR maximization is transformed to Rayleigh-Ritz quotient, resulting in a closed-form solution. Interference minimization and SNR balancing are reformulated as secondary-order cone programming (SOCP) problems. These problems can be solved efficiently using interior point methods. Several numerical simulation examples
are provided to illustrate effectiveness of our approaches.

Key words: cognitive radio, tracing, beamforming, secondary-order cone programming (SOCP), particle filter

CLC Number:

TN911.73

GUO Yan, ZHU Fang-jun, LI Ning. Dynamic Beamforming in Cognitive Radio Networks[J]. Journal of Applied Sciences, 2015, 33(3): 223-233.

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Dynamic Beamforming in Cognitive Radio Networks

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