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Pattern analysis of uniform circular array
Du, K.-L.;
Antennas and Propagation, IEEE Transactions on
Volume: 52 , Issue: 4
Digital Object Identifier: 10.1109/TAP.2004.825802
Publication Year: 2004 , Page(s): 1125 - 1129
IEEE Journals
Abstract | Full Text: PDF (408 KB)
Quick Abstract
The radiation characteristics of a uniform circular array with linear centrally-fed dipole elements, used for smart antenna systems, are analyzed in this paper. The radiation patterns of the array and the gain of the array over a single element are derived based on the thin-wire model. Numerical simulations using the thin-wire model and the method of moments (MoM) have been conducted and compared for a half-wavelength dipole array. Simulations using the MoM demonstrate that the wire diameter of the elements has no significant effect on normalized azimuthal and elevation patterns for a given pattern design. Normalized azimuthal patterns by the thin-wire model and the MoM are in good agreement with each other, while normalized elevation patterns by the thin-wire model are inaccurate since mutual coupling is not considered in the model. Wire diameter affects the radiation resistance and thus determines the amplitude of the radiation field.
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Affordable Cyclostationarity-Based Spectrum Sensing for Cognitive Radio With Smart Antennas
Du, K.-L.; Wai Ho Mow;
Vehicular Technology, IEEE Transactions on
Volume: 59 , Issue: 4
Digital Object Identifier: 10.1109/TVT.2010.2043860
Publication Year: 2010 , Page(s): 1877 - 1886
IEEE Journals
Abstract | Full Text: PDF (332 KB)
Quick Abstract
Cognitive radio (CR) technology is a promising way to improve the bandwidth efficiency of underutilized radio spectra. For practical CR systems with limited a priori knowledge of the primary users' signal characteristics, spectrum sensing is mainly based on energy detection and cyclostationary feature detection. Energy detection is simple and practical but becomes ineffective at a low signal-to-interference-and-noise ratio (SINR). Conventional cyclostationary feature detection based on cyclic spectrum estimation can robustly detect weak signals from primary users by only exploiting the cyclostationarity property of communication signals. However, the high implementation complexity it requires limits its widespread usage. In the literature, the use of smart-antenna technology is suggested to track the locations of the primary users and apply transmit beamforming to avoid spatial interference with their signals. The objective of this paper is to establish adaptive cyclostationary (receive) beamforming as an effective spectrum-sensing method with affordable complexity for multiple-antenna cognitive radio. Specifically, we introduce a new spectrum-sensing method that exploits a recently proposed beamforming algorithm, called the adaptive cross-self-coherent-restoral (ACS) algorithm. The complexity of the resultant algorithm is higher than that of the energy detector but is at least an order of magnitude smaller than that of the previous cyclostationary feature detectors, such as the Fourier spectrum cyclic density analysis method and its multitaper-Loe¿ve version. Their performances for spectrum sensing are empirically evaluated and compared in detail in an example.