Quad-Port MIMO Filtenna With High Isolation Employing BPF With High Out-of-Band Rejection

Elsharkawy, Rania R.; El-Hameed, Anwer S. Abd; El-Nady, Shaza

doi:10.1109/access.2021.3134865

Cited by 21 publications

(4 citation statements)

References 34 publications

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“…of Ports Notch Freq. (GHz) Isolation (dB) [37] 19 × 30 (= 570) The diversity characteristic of the quad-element 2D MIMO antenna have been determined in terms of envelope correlation coefficient (ECC), diversity gain (DG), and total active reflection coefficient (TARC), computed using the formulas in [42]. To ensure high diversity among constituent individual MIMO antenna elements, it is desired to maintain the range of ECC lower than 0.5 and TARC value lower than 0 dB, respectively.…”

Section: Fig 5 Comparison Between Hmvrvr and Other ML Algorithms For ...mentioning

confidence: 99%

Machine Learning Assisted Hybrid Electromagnetic Modeling Framework and Its Applications to UWB MIMO Antennas

et al. 2023

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Machine learning (ML) has gained recognition as an efficient and robust technique to realize the solution of electromagnetic forward and inverse problems. This article introduces a hybrid ML framework that simultaneously acts as a forward and inverse model based on a mode input. Multivariate relevance vector regression (MVRVR) is adopted for implementing the hybrid ML model. MVRVR models for forward and inverse modeling are also presented. In addition, three hybrid ML models based on support vector regression (SVR), Gaussian process regression (GPR), and artificial neural network (ANN) are also implemented and a thorough comparative analysis between these ML models with the proposed MVRVR model is investigated to verify its accuracy. The proposed hybrid framework can be used to replace the requirements of the two separate models for solving forward and inverse problems. Two examples of ultrawideband (UWB) MIMO antennas are employed to validate the effectiveness of the proposed modeling framework.INDEX TERMS Machine learning, MIMO antenna, multivariate relevance vector regression (MVRVR), ultra-wideband (UWB)

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Section: Fig 5 Comparison Between Hmvrvr and Other ML Algorithms For ...mentioning

confidence: 99%

Machine Learning Assisted Hybrid Electromagnetic Modeling Framework and Its Applications to UWB MIMO Antennas

et al. 2023

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“…In existing literature [13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31], dual-polarization antennas have been designed by employing orthogonal feeding structures to excite the antenna [13], [14]. Achieving adequate isolation between the two ports of the dual-polarization antenna is crucial for optimal performance.…”

Section: Introduction mentioning

confidence: 99%

Dual Polarized Antenna with Wide Beamwidth Utilizing TM01 Mode for X-Band Applications

Mohy,

Abd El-Hameed,

Atallah

et al. 2024

SVU-International Journal of Engineering Sciences and Applicati

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This paper presents a triple-port dual-polarized antenna designed for X-band applications with a wide beamwidth. The antenna utilizes 50 Ω probe feeding structure, resulting in a small size of 20 × 20 mm 2 . The proposed antenna is developed for X-band applications, operating at 10.7 GHz with a bandwidth of 200 MHz. The structure comprises two stacked substrates with electrical properties (2.2, and 4.5 permittivities, 1.5 mm height). The top layer features a rectangular patch with two ports for exciting orthogonal polarizations, while the middle layer includes a circular patch serving as a ground plane for the rectangular patch. The excitation of TM01 mode in the circular patch generates a conical radiation pattern, and the antenna exhibits an overlapping bandwidth from 10.3 GHz to 10.9 GHz. The peak gains, illustrated over the frequency range, reach 5.2 dBi for the circular patch and 7 dBi for the rectangular patch. Fabrication and measurements of the antenna demonstrate good agreement between experimental and simulation results.

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“…An EBG structure is based on the metamaterial used to isolate UWB antenna for X, Ku, K, and Ka-band applications with maximum isolation of 37 dB [25]. A filtenna uses a COVID-19 shaped structure for UWB applications with an isolation of −30 dB [26]. Metamaterial with near zero refractive index (NZRI) and DNG property-based square SRR (SSRR) unit cells is utilized for quad-band applications [27].…”

Section: Introductionmentioning

confidence: 99%

Isolation Analysis of Miniaturized Metamaterial-based MIMO Antenna for X-band Radar Applications Using Machine Learning Model

Undrakonda¹,

Upadhyayula²

2022

PIER C

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A novel metamaterial-based circular patch multi-input multi-output (MIMO) antenna is designed with a 'C'-shaped defected ground structure for high isolation. A 4 × 4 mm 2 unit cell for a ring resonator has been designed and exhibited double negative material (DNG) properties from 1.0 to 2.92 GHz and 13.68 to 17.67 GHz and Mu negative material (MNG) from 4.70 to 13.67 GHz. The proposed antenna structure is designed by embedding the ring resonator-based meta-structure to a circular patch antenna and fabricated with dimensions 0.245λ 0 × 0.409λ 0 (15 × 25 mm 2 ). The proposed antenna operating at 8.50 to 14.23 GHz for X and lower Ku bands is used in the Unmanned Arial Vehicle (UAV's) applications. The spacing between elements is 0.088λ 0 (5.4 mm) on an FR4 epoxy substrate, and the 'C'-shaped structure on the back of the antenna improves the isolation of more than 24 dB in the operating band. Distance between the antenna elements plays a crucial role, and parameters affected by this are optimized by introducing machine learning. For future predictions, a linear regression model was created to optimize the parameters' linear dependencies like isolation and return loss on the distance between the antenna elements. The radiation efficiency and gain of the antenna are enhanced by 92% and 6.02 dB at 13.22 GHz, respectively. The MIMO antenna's simulated results of diversity and other parameters are in the acceptable range with the measured results used for X-band radar applications. The proposed decoupling technique is simple to understand and implement.

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Quad-Port MIMO Filtenna With High Isolation Employing BPF With High Out-of-Band Rejection

Cited by 21 publications

References 34 publications

Machine Learning Assisted Hybrid Electromagnetic Modeling Framework and Its Applications to UWB MIMO Antennas

Machine Learning Assisted Hybrid Electromagnetic Modeling Framework and Its Applications to UWB MIMO Antennas

Dual Polarized Antenna with Wide Beamwidth Utilizing TM01 Mode for X-Band Applications

Isolation Analysis of Miniaturized Metamaterial-based MIMO Antenna for X-band Radar Applications Using Machine Learning Model

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