Maximum gain of Yagi–Uda arrays

Bojsen, J.; Schjær-Jacobsen, Hans; Nilsson, Emil; Andersen, Jørgen Bach

doi:10.1049/el:19710360

Cited by 39 publications

(26 citation statements)

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“…This can be recognized as a director mode since the beam extends away from the driven antenna in the direction of the parasitic antennas. In [13], the optimization is performed for this gain maximum, and this mode has been used conventionally to enhance the antenna gain, however it corresponds to the minimum capacity point shown in Fig. 6.…”

Section: Resultsmentioning

confidence: 99%

“…The channel capacity is maximized by changing the electric lengths of the parasitic antennas virtually; this reduces the number of measurements since only the basic antenna configuration needs to be measured. In [13], the Yagi-Uda array is optimized using reactive termination, but it only focused the gain of the Yagi-Uda array. In order to find out fixed radiation pattern that maximize the channel capacity, the channel information and antenna characteristics must be combined.…”

Section: Introductionmentioning

confidence: 99%

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A Stochastic Approach to Design MIMO Antenna with Parasitic Elements Based on Propagation Characteristics

Honma

Nishimori

Kudo

et al. 2010

IEICE Trans. Commun.

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SUMMARYThis paper proposes a channel capacity maximization method for Multiple-Input Multiple-Output (MIMO) antennas with parasitic elements. Reactive terminations are connected to the parasitic elements, and the reactance values are determined to achieve stochastically high channel capacity for the environment targeted. This method treats the S-parameter and propagation channel of the antenna, including the parasitic elements, as a combined circuit. The idea of the 'parasitic channel,' which is observed at the parasitic antenna, is introduced to simplify the optimization procedure. This method can significantly reduce the number of necessary measurements of the channel for designing the antenna. As a design example, a bidirectional Yagi-Uda array, which has two driven antennas at both ends of the linear array, is measured in an indoor environment. The resulting design offers enhanced channel capacity mainly due to its improved signal-to-noise ratio compared to the antenna without the parasitic antennas.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Stochastic Approach to Design MIMO Antenna with Parasitic Elements Based on Propagation Characteristics

Honma

Nishimori

Kudo

et al. 2010

IEICE Trans. Commun.

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“…Since its invention, continuous efforts have been put in optimizing its design for desired gain, impedance, SLL and bandwidth, etc., requirements using different optimization techniques based on traditional mathematical approaches [24,4,8,25,7,6,9] and Artificial Intelligence (AI) techniques [16,35,34,3,19,31,30].…”

Section: Introductionmentioning

confidence: 99%

“…Bojsen et al in [4] proposed another optimization technique to calculate the maximum gain of Yagi-Uda antenna arrays with equal and unequal spacings between adjoining elements. Cheng et al in [7] and [6] have used optimum wire lengths and their spacings to maximize the gain of the Yagi-Uda antenna.…”

Section: Introductionmentioning

confidence: 99%

Multi-objective Gain-Impedance Optimization of Yagi-Uda Antenna using NSBBO and NSPSO

Singh¹,

Mittal²,

Sachdeva³

2012

IJCA

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Biogeography-Based Optimization (BBO) is a population based algorithm which has shown impressive performance over other Evolutionary Algorithms (EAs). BBO algorithm is based on the study of distribution of biological organisms over space and time. YagiUda antenna design is most widely used antenna at VHF and UHF frequencies due to high gain, directivity and ease of construction. However, designing a Yagi-Uda antenna, that involves determination of optimal wire-lengths and their spacings, is highly complex and non-linear engineering problem. It further complicates as multiple objectives, viz. gain, and impedance, etc., are required to be optimized due to their conflicting nature, i.e., reactive antenna impedance increases significantly as antenna gain is intended to increase. In this paper Non-dominated Sorting BBO (NSBBO) is proposed and where standard and blended variants of BBO are investigated in optimizing six-element Yagi-Uda antenna designs for multiple objectives, viz., gain and impedance, where ranking of potential solutions is done using non-dominated sorting. The simulation results of BBO variants and Particle Swarm Optimization (PSO) are presented in the ending sections of the paper that depict clearly that NSBBO with blended migration operator is best option among all.

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“…However, the antenna size is still large (5.2λ × 4λ). The Yagi-Uda antenna was used excessively as a good candidate for high gain [9][10][11]. However, this antenna has limited gain up to 18 dB range, which can sometimes prove limiting in some remote applications.…”

Section: Introductionmentioning

confidence: 99%

Design of a High-Gain Cavity-Backed Slot Antenna With Mushroom Cells and Bent Ground Walls

Eldek¹

2011

PIER Letters

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Maximum gain of Yagi–Uda arrays

Cited by 39 publications

References 1 publication

A Stochastic Approach to Design MIMO Antenna with Parasitic Elements Based on Propagation Characteristics

A Stochastic Approach to Design MIMO Antenna with Parasitic Elements Based on Propagation Characteristics

Multi-objective Gain-Impedance Optimization of Yagi-Uda Antenna using NSBBO and NSPSO

Design of a High-Gain Cavity-Backed Slot Antenna With Mushroom Cells and Bent Ground Walls

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