The Analysis of a Reconfigurable Antenna With a Rotating Feed Using Graph Models

Costantine, J.; Al-Saffar, Sinan; Christodoulou, C.G.; Kabalan, Karim Y.; El‐Hajj, Ali

doi:10.1109/lawp.2009.2029137

Cited by 13 publications

(3 citation statements)

References 8 publications

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“…Applying NNs on a reconfigurable star antenna with 6 switches connecting different parts together [38] results in 6 input neurons, 11 hidden neurons, and 51 output neurons. The antenna structure is shown in Figure 107, and its NN structure is represented in Figure 108.…”

Section: Star Antennamentioning

confidence: 99%

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FGPA Mission Assurance Center (FMAC) Support Activity at the University of New Mexico

Christodoulou

2013

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Section: Star Antennamentioning

confidence: 99%

“…Graph modeling reconfigurable antennas transform them into software accessible devices [24,38] that are easy to optimize, control and automate. In addition to these functionalities the modeling of reconfigurable antennas using graphs leads to a redundancy reduction approach that eliminates unnecessary components from the structure.…”

Section: Graph Modelingmentioning

confidence: 99%

FGPA Mission Assurance Center (FMAC) Support Activity at the University of New Mexico

Christodoulou

2013

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“…Antenna in[5] with its graph model NN structure for the antenna in[5] Antenna structure and graph model after the removal of 2 redundant switchesFigure 10Antenna structure and graph model[6] …”

mentioning

confidence: 99%

Applying graph models and Neural Networks on reconfigurable antennas for cognitive radio applications

Costantine

Tawk

Zuraiqi

et al. 2011

2011 IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications

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In this paper, graph models and Neural Networks (NNs) are applied to reconfigurable antennas and both techniques are analyzed to be used for cognitive radio applications. The use of NNs to synthesize different antenna configurations and the use of graph models to optimize the performance of such configurations are addressed and investigated. The application of both tools on reconfigurable antennas has proven to be beneficial in applications where software control and fast response are required. Thus the incorporation of such techniques on an FPGA ( Field Programmable Gate Array) creates a self adjusting software defined antenna that can be applied to many wireless communication applications such as cognitive radio.

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Defected waveguide structure designs and characteristics

Chin

Aziz

Ahmad

2019

Micro & Optical Tech Letters

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This article presented defected waveguide structure (DWS) designs and characteristics with microstrip‐fed circular monopole antenna for ultrawideband applications. Typically, waveguide is often designed and employed as antenna and filter application in its rigid dimension. The reconfigurable design toward the waveguide in terms of structural alteration with DWS was found less concerned among researchers although defected ground structure and defected microstrip structure have been applied widely. The motivation of this article was to propose the different DWS designs and characteristics in terms of the S‐parameters result. DWS in basic square geometry with different configurations of straight lines were introduced and compared with FR4 substrate waveguide. Simulated S‐parameters results were modeled in terms of equivalent circuit and measured for validation. For practical measurement, waveguide ports at both open‐ended surface of waveguide were replaced by the monopole antenna. For the modeled S‐parameters results, the square DWS design and square DWS with horizontal straight lines showed quite similar characteristics with higher S11 and lower S21 above frequency 9 GHz. Whereas square DWS with vertical straight lines and square DWS with both horizontal vertical straight lines showed higher S11 and lower S21 below frequency 3.5 GHz. Square DWS with vertical straight lines achieved the lowest S21 around −70 dB below 3.5 GHz and lower S21 around −50 dB at frequency 10.3 GHz. Thus, DWS is proposed for the future smart antenna technology as it can be further modified to meet the different requirements without changing the antenna configuration.

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The Analysis of a Reconfigurable Antenna With a Rotating Feed Using Graph Models

Cited by 13 publications

References 8 publications

FGPA Mission Assurance Center (FMAC) Support Activity at the University of New Mexico

FGPA Mission Assurance Center (FMAC) Support Activity at the University of New Mexico

Applying graph models and Neural Networks on reconfigurable antennas for cognitive radio applications

Defected waveguide structure designs and characteristics

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