14 research outputs found
Machine learning-based technique for gain prediction of mm-wave miniaturized 5G MIMO slotted antenna array with high isolation characteristics
No full textThis study presents the design and analysis of a compact 28GHz MIMO antenna for 5G wireless
networks, incorporating simulations, measurements, and machine learning (ML) techniques to
optimize its performance. With dimensions of 3.19 λ₀×3.19 λ₀, the antenna offers a bandwidth of
5.1GHz, a peak gain of 9.43 dBi, high isolation of 31.37 dB, and an efficiency of 99.6%. Simulations
conducted in CST Studio were validated through prototype measurements, showing strong agreement
between the measured and simulated results. To further validate the design, an equivalent RLC circuit
model was developed and analyzed using ADS, with the reflection coefficient results closely matching
those from CST. Additionally, supervised ML techniques were employed to predict the antenna’s gain,
evaluating nine models using metrics such as R-squared, variance score, mean absolute error, and root
mean squared error. Among the models, Random Forest Regression achieved the highest accuracy,
delivering approximately 99% reliability in gain prediction. This integration of machine learning with
antenna design underscores its potential to optimize performance and enhance design efficiency.
With its compact size, high isolation, and exceptional efficiency, the proposed antenna is a promising
candidate for 28GHz 5G applications, offering innovative solutions for next-generation wireless
communication
Performance improvement of THz MIMO antenna with graphene and prediction bandwidth through machine learning analysis for 6G application
No full textThis article provides the findings of a study that integrated simulation, an RLC equivalent circuit, and machine learning (ML) techniques to improve wireless indoor communications clusters with future 6 G applications. The antenna being presented is constructed on a polyimide substrate. It exhibits an isolation of 27 dB and has a bandwidth of 4.331 THz, ranging from 0.631 THz to 4.962 THz. Along with its small size (95.52 × 227.24) µm2, it boasts an impressive maximum gain of 13.3 dB and an efficiency rating of 95 %. The ECC value drops below 0.0002 when the DG goes over 9.99. An advanced design system (ADS) creates a model like the proposed MIMO antenna to compare the return loss caused by CST (Computer Simulation Technology). Subsequently, following extensive data sampling with CST MWS (Microwave Studio) simulation, we employed supervised regression ML techniques. Gaussian process regression demonstrates exceptional accuracy, reaching almost 99 %, as evidenced by the high R-square and var scores. Additionally, it achieves the lowest error, less than one, while predicting bandwidth. The proposed antenna demonstrates strong potential as a formidable contender for 6 G THz band applications, as evidenced by the outcomes of the CST simulations and the prognostications derived from the machine learning techniques
Machine learning based compact MIMO antenna array for 38 GHz millimeter wave application with robust isolation and high efficiency performance
No full textThe performance of wireless 5 G communication networks can be enhanced by combining multiple-input multiple-output (MIMO) antennas with machine learning (ML). The suggested antenna, which is constructed on a Rogers 5880 substrate, is well-suited for usage in the high bands of 5 G applications due to its 27 dB isolation and bandwidth of 35.181–39.689 (4.508) GHz within a -10 dB range. Besides being compact (measuring 37 mm × 24 mm), it boasts an impressive maximum gain of 8.09 dB and an efficiency level of 98.2 %. The methods explored in this research are the RLC equivalent circuit model and simulations with validated measurements. An advanced design system (ADS) is utilized to compare the return loss because of CST to create a model like the suggested MPA. The next step is extensive data sampling using CST MWS simulation, followed by applying supervised regression ML techniques. Lasso regression yields excellent results in terms of accuracy and achieves the lowest degree of error when testing the bandwidth prediction. Considering everything, the antenna stands out as a top choice for the 5 G communication system's high band. Designing a small MIMO antenna for 38 GHz mm-wave 5 G applications presents challenges because it requires balancing high performance while minimizing mutual coupling between closely spaced elements and dealing with high-frequency complexities
Broadband high gain performance MIMO antenna array for 5 G mm-wave applications-based gain prediction using machine learning approach
No full textThis paper presents the findings about implementing a machine learning (ML) technique to optimize the performance of 5 G mm wave applications utilizing multiple-input multiple-output (MIMO) antennas operating at
the 28 GHz frequency band. This article examines various methodologies, including simulation, measurement,
and the utilization of an RLC-equivalent circuit model, to evaluate the appropriateness of an antenna for its
intended applications. In addition to its compact dimensions, the proposed design exhibits a maximum gain of
10.34 dBi, superior isolation exceeding 26 dB, and a broad bandwidth of 16.56 % Centered at 28 GHz and
spanning from 25.905 to 30.544 GHz. Another supervised regression machine learning technique is utilized to
predict the antenna’s gain accurately. Machine learning (ML) models can be assessed by several measures, such
as the variance score, R square, mean square error (MSE), mean absolute error (MAE), root mean square error
(RMSE), and Mean Absolute Percentage Error (MAPE). Among the six machine learning models considered, it is
seen that the Gaussian Process Regression (GPR) model exhibits the lowest error and achieves the highest level of
accuracy in forecasting gain. The antenna under consideration has promising qualities for its intended use in
high-band 5 G applications. This is evidenced by the modelling findings obtained from Computer Simulation
Technology (CST) and Advanced Design System (ADS)and the measured and projected results derived using
machine learning methodologies
Graphene-based THz antenna with a wide bandwidth for future 6G short-range communication
Full text linkIn this study, we present the design and investigation of a terahertz (THz) frequency antenna optimized for the 2-10 THz range, featuring both single-element and multiple-input multiple-output (MIMO) configurations, with a focus on industrial and innovative applications to enhance future 6G communication systems. The antenna, constructed on a polyimide substrate with dimensions of 90×30 µm, achieves a bandwidth from 4.0328 to 10 THz. The MIMO configuration, which includes two ports, demonstrates excellent isolation with a value of -27 dB. The proposed antenna system achieves a gain of 12.38 dB and an efficiency of 89%, making it highly appropriate for THz communication applications. Furthermore, the envelope correlation coefficient (ECC) of 0.002 and diversity gain (DG) of 9.99 affirm the antenna’s effectiveness in MIMO systems. A resistance inductance capacitance (RLC) circuit model was employed to accurately represent the S11 curve, ensuring precise characterization of the antenna’s performance. These results underscore the probability of the proposed antenna for high-speed, short-range communication systems
A multiband sub-6 THz patch antenna with high gain for IoT and 6G communication
Full text linkThis comprehensive study introduces a meticulously designed and characterized terahertz (THz) multiple-input multiple-output (MIMO) antenna engineered to operate within the 0.4 THz to 1.6 THz frequency range. The antenna’s construction includes a copper patch and ground plane integrated into a polyimide substrate, ensuring exceptional durability and robust performance. Significantly, the antenna reveals four distinct resonance frequencies at 0.46 THz, 0.9 THz, 1.31 THz, and 1.44 THz each accompanied by bandwidths of 0.005 THz, 0.17 THz, and 0.34 THz, respectively. Moreover, the antenna delivers notable gains of 8.52 dB, 11.54 dB, and 13.25 dB at these frequencies, coupled with substantial efficiencies of 88.32%, 92.02%, and 89.89%, respectively. Additionally, the antenna showcases exceptional isolation of 26 dB, a low envelope correlation coefficient (ECC) of 0.003, and a diversity gain (DG) of 9.98. These remarkable attributes underscore the antenna’s aptness for high-performance THz applications, offering substantial advantages in terms of gain, efficiency, and isolation for next-generation wireless communication systems
A novel-shaped THz MIMO antenna with high bandwidth for advanced 6G wireless application
Full text linkThis article presents an industrial and innovation highly efficient drone shaped slotted graphene-based multiple input multiple output (MIMO) antenna with improved isolation, designed for high-speed short-range communication, video rate imaging, medical imaging, and explosive detection in the THz band. The proposed antenna is constructed on an 88×244 μm2 polyimide substrate. Key performance parameters such as reflection coefficient, gain, directivity, radiation pattern, and antenna efficiency are evaluated at the resonating frequencies of 1.7 THz, 3.35 THz, and 5.31 THz, covering a wide bandwidth of 4.88 THz with a reflection coefficient of less than -10 dB. The antenna achieves a maximum gain of 13.92 dB and a radiation efficiency of 95.77% within the resonating band. The MIMO design parameters include an envelope correlation coefficient (ECC) of 0.00015, a diversity gain (DG) of 9.9992, and an isolation of less than -31.55 dB between its elements across the entire bandwidth. The outcomes from CST simulations were verified by designing and simulating a similar resistance-inductance-capacitance (RLC) circuit in advanced design system (ADS), with both simulators producing comparable reflection coefficients. These features underscore the potential of the proposed antenna, utilizing simulations and an equivalent RLC circuit model, as a robust candidate for THz band applications in 6G wireless communication
A 6G THz MIMO antenna with high gain and wide bandwidth for high-speed wireless communication
Full text linkThis study presents a comprehensive industrial and innovation design and thorough analysis of a terahertz (THz) multiple-input multiple-output (MIMO) antenna, addressing the increasing demand for high-performance multi-antenna systems in THz communication applications. The primary objective of this research is to develop a compact and efficient MIMO antenna that operates over a wide frequency range and provides high isolation, specifically within the 1–10 THz spectrum. The proposed antenna achieves an impressive total bandwidth of approximately 9 THz, featuring seven distinct resonance frequencies at 1.39 THz, 3.26 THz, 4.72 THz, 5.96 THz, 7.07 THz, 8.194 THz, and 9.426 THz. The design employs a polyimide substrate and a graphene patch. Key performance metrics include a maximum gain of 15 dB, efficiency of 99.8%, and isolation values that range from 28 dB to 63 dB. An resistor inductor capacitor (RLC) equivalent circuit using advanced design system (ADS) software. Additionally, the antenna displays remarkable diversity metrics, with an envelope correlation coefficient (ECC) of 0.000778 and a diversity gain of 9.99961 dB. With compact dimensions of (65×180) µm2 and outstanding performance characteristics, this design is confirmed to be suitable for THz applications, fulfilling the research goal of facilitating efficient and reliable communication in sophisticated multi-antenna systems
ANN-based performance estimation of a slotted inverted F-shaped tri-band antenna for satellite/mm-wave 5G application
Full text linkIn this research, we explain comprehensive industrial and innovation results on using an artificial neural network (ANN) method to improve the performance of microstrip patch antennas for 5G, indoor-outdoor, and Ku band uses. To determine if an antenna is appropriate, this article discusses multiple methods, one of which is to do a simulation using validating software like high frequency structure simulator (HFSS) and Altair Feko. Based on the Rogers RT 5880 substrate, the antenna is constructed. There is a loss tangent of 0.0009 and its dimensions are 17.1053 mm in length and 16 mm in width. Its dielectric constant is 2.2. Despite its small size, it boasts an impressive maximum efficiency of almost 90% and a gain of approximately 8 dB. As an indicator of ANN model performance, we may look at the R-squared value (99%), the mean square error (MSE), which is approximately 0.0015, and the confidence interval (99%). The ANN models are the most accurate and have the lowest error rate when it comes to predicting efficiency and gain. The suggested antenna is a promising contender for the targeted Ku band, indoor/outdoor, and 5G uses, as verified by the clustering of computer simulation technology (CST), HFSS, and Altair Feko simulated results with the measured and predicted outcomes of ANN approac
Graphene-based high-gain MIMO antenna for enhanced 6G wireless communication systems
Full text linkThis paper presents a novel design and analysis of a high-performance multiple-input multiple-output (MIMO) terahertz (THz) antenna intended for next-generation sixth-generation (6G) wireless communication systems. The proposed antenna operates over a wide frequency range of 1 THz to 4.9 THz, achieving a broad bandwidth of 3.9 THz with three distinct resonant frequencies at 2.05 THz, 3.9 THz, and 4.52 THz, each exhibiting excellent return loss characteristics. The antenna features a graphene-based patch with a copper ground plane, etched on a polyimide substrate with a dielectric constant (εr) of 3.5 and a thickness of 10 micrometers (μm). Key performance metrics, including a high gain of 15.9 decibels (dB), an efficiency of 95.95%, an envelope correlation coefficient (ECC) of 0.0005, and a diversity gain (DG) of 9.997 dB, indicate outstanding performance. The measured isolation between the two antenna elements is -31.91 dB, signifying excellent isolation. An equivalent resistor-inductor-capacitor (RLC) circuit model is developed using advanced design system (ADS), validated by comparing S11 results from both computer simulation technology (CST) and ADS simulations. The proposed MIMO antenna’s wide operating range and robust performance demonstrates great potential for high-speed THz wireless communication, imaging, spectroscopy, sensing, and offers valuable contributions to industry and innovation
