Pub Date : 2021-07-05DOI: 10.1109/MOCAST52088.2021.9493369
Stylianos Voutsinas, D. Karolidis, I. Voyiatzis, M. Samarakou
During the last decade, exponential growth in energy production by Photovoltaic systems (PVS) has been observed. Although very promising concerning energy production, PVS are often prone to faults that arise either due to environmental conditions or to the quality of materials used for their manufacturing and handling during installation. If these faults are left untreated, a risk arises both to the operation of the system itself (risk of destruction) and to its very ability to produce energy reliably. This paper discusses methods for fault detection and identification on the DC side of the photovoltaic systems. The methods are studied for their ability to identify various fault types as well as their complexity and limitations.
{"title":"Photovoltaic Faults: A comparative overview of detection and identification methods","authors":"Stylianos Voutsinas, D. Karolidis, I. Voyiatzis, M. Samarakou","doi":"10.1109/MOCAST52088.2021.9493369","DOIUrl":"https://doi.org/10.1109/MOCAST52088.2021.9493369","url":null,"abstract":"During the last decade, exponential growth in energy production by Photovoltaic systems (PVS) has been observed. Although very promising concerning energy production, PVS are often prone to faults that arise either due to environmental conditions or to the quality of materials used for their manufacturing and handling during installation. If these faults are left untreated, a risk arises both to the operation of the system itself (risk of destruction) and to its very ability to produce energy reliably. This paper discusses methods for fault detection and identification on the DC side of the photovoltaic systems. The methods are studied for their ability to identify various fault types as well as their complexity and limitations.","PeriodicalId":146990,"journal":{"name":"2021 10th International Conference on Modern Circuits and Systems Technologies (MOCAST)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127106578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-05DOI: 10.1109/MOCAST52088.2021.9493368
Anastasios Vlachos, Nikos Temenos, P. Sotiriadis
A soft-filtering processing architecture based on Sigma-Delta Modulation and Stochastic Computing is proposed. It converts a high-resolution signal using a first order digital Sigma-Delta Modulator into a single-bit one and then exploits Stochastic Computing’s encoding to perform area-efficient multiplications. The Sigma-Delta Modulator allows for the input signal to be oversampled at a much higher frequency rate, offering improved performance in terms of SNR, which is not possible with standard Stochastic Computing filter realizations. Spectral simulations results demonstrate the proper signal quantization and operation of the filter, including the filter’s roll-off behavior. FPGA synthesis results of the proposed architecture, illustrate its area advantages in comparison to conventional binary filtering.
{"title":"Exploring the Effectiveness of Sigma-Delta Modulators in Stochastic Computing-Based FIR Filtering","authors":"Anastasios Vlachos, Nikos Temenos, P. Sotiriadis","doi":"10.1109/MOCAST52088.2021.9493368","DOIUrl":"https://doi.org/10.1109/MOCAST52088.2021.9493368","url":null,"abstract":"A soft-filtering processing architecture based on Sigma-Delta Modulation and Stochastic Computing is proposed. It converts a high-resolution signal using a first order digital Sigma-Delta Modulator into a single-bit one and then exploits Stochastic Computing’s encoding to perform area-efficient multiplications. The Sigma-Delta Modulator allows for the input signal to be oversampled at a much higher frequency rate, offering improved performance in terms of SNR, which is not possible with standard Stochastic Computing filter realizations. Spectral simulations results demonstrate the proper signal quantization and operation of the filter, including the filter’s roll-off behavior. FPGA synthesis results of the proposed architecture, illustrate its area advantages in comparison to conventional binary filtering.","PeriodicalId":146990,"journal":{"name":"2021 10th International Conference on Modern Circuits and Systems Technologies (MOCAST)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126020368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-05DOI: 10.1109/MOCAST52088.2021.9493388
Vasileios P. Rekkas, S. Sotiroudis, P. Sarigiannidis, G. Karagiannidis, S. Goudos
Wireless communication systems play a very crucial role for business, commercial, health and safety applications. With the commercial deployment of fifth generation (5G), academic and industrial research focuses on the sixth generation (6G) of wireless communication systems. Artificial Intelligence (AI) and especially Machine Learning (ML), will be a key component of 6G systems. Here, we present an up-to-date review of future 6G wireless systems and the role of unsupervised ML techniques in them.
{"title":"Unsupervised Machine Learning in 6G Networks -State-of-the-art and Future Trends","authors":"Vasileios P. Rekkas, S. Sotiroudis, P. Sarigiannidis, G. Karagiannidis, S. Goudos","doi":"10.1109/MOCAST52088.2021.9493388","DOIUrl":"https://doi.org/10.1109/MOCAST52088.2021.9493388","url":null,"abstract":"Wireless communication systems play a very crucial role for business, commercial, health and safety applications. With the commercial deployment of fifth generation (5G), academic and industrial research focuses on the sixth generation (6G) of wireless communication systems. Artificial Intelligence (AI) and especially Machine Learning (ML), will be a key component of 6G systems. Here, we present an up-to-date review of future 6G wireless systems and the role of unsupervised ML techniques in them.","PeriodicalId":146990,"journal":{"name":"2021 10th International Conference on Modern Circuits and Systems Technologies (MOCAST)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114831692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-05DOI: 10.1109/MOCAST52088.2021.9493353
Cristian E. Onete, M. Onete
In this paper we present two topological nodes transformations that preserve the main properties of a network. A third transformation that may change the Hamiltonicity status is introduced, too. The three transformations are related to cubic planar networks in general and to bi-partite cubic networks, respectively. The complexity of the related algorithm is presented, too.
{"title":"Extending Two Classes Of Networks Using Three Topological Transformations","authors":"Cristian E. Onete, M. Onete","doi":"10.1109/MOCAST52088.2021.9493353","DOIUrl":"https://doi.org/10.1109/MOCAST52088.2021.9493353","url":null,"abstract":"In this paper we present two topological nodes transformations that preserve the main properties of a network. A third transformation that may change the Hamiltonicity status is introduced, too. The three transformations are related to cubic planar networks in general and to bi-partite cubic networks, respectively. The complexity of the related algorithm is presented, too.","PeriodicalId":146990,"journal":{"name":"2021 10th International Conference on Modern Circuits and Systems Technologies (MOCAST)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116854701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-05DOI: 10.1109/MOCAST52088.2021.9493361
Dimitrios Danopoulos, Konstantinos Anagnostopoulos, C. Kachris, D. Soudris
Accurate and efficient Machine Learning algorithms are of vital importance to many problems, especially on classification or clustering tasks. In recent years, a new class of Machine Learning has been introduced called Generative Adversarial Network (GAN) which relies on two neural networks: a generative network (generator) and a discriminative network (discriminator). These two networks compete with each other with aim to generate new data such as images. For example, a GAN is capable of reconstructing an image which is filled by noise or has some regions damaged. Image reconstruction has found its application in the field of computer vision, augmented reality, human computer interaction and animation as well as medical imaging. However, this type of algorithm requires many MAC (multiply-accumulate) operations and high power consumption to operate. In this work, we implement an Image reconstruction algorithm with GANs, specifically as a case study we train a model capable of restoring clothing images based on the fashion-MNIST dataset. Additionally, we implement and accelerate it on a Xilinx FPGA SoC which as platforms are proven to address these kind of problems very efficiently in terms of performance and power. The design also achieves better performance and power efficiency from CPU and GPU with 0.013 ms average reconstruction time per image and 43 db PSNR on the FPGA quantized configuration.
{"title":"FPGA Acceleration of Generative Adversarial Networks for Image Reconstruction","authors":"Dimitrios Danopoulos, Konstantinos Anagnostopoulos, C. Kachris, D. Soudris","doi":"10.1109/MOCAST52088.2021.9493361","DOIUrl":"https://doi.org/10.1109/MOCAST52088.2021.9493361","url":null,"abstract":"Accurate and efficient Machine Learning algorithms are of vital importance to many problems, especially on classification or clustering tasks. In recent years, a new class of Machine Learning has been introduced called Generative Adversarial Network (GAN) which relies on two neural networks: a generative network (generator) and a discriminative network (discriminator). These two networks compete with each other with aim to generate new data such as images. For example, a GAN is capable of reconstructing an image which is filled by noise or has some regions damaged. Image reconstruction has found its application in the field of computer vision, augmented reality, human computer interaction and animation as well as medical imaging. However, this type of algorithm requires many MAC (multiply-accumulate) operations and high power consumption to operate. In this work, we implement an Image reconstruction algorithm with GANs, specifically as a case study we train a model capable of restoring clothing images based on the fashion-MNIST dataset. Additionally, we implement and accelerate it on a Xilinx FPGA SoC which as platforms are proven to address these kind of problems very efficiently in terms of performance and power. The design also achieves better performance and power efficiency from CPU and GPU with 0.013 ms average reconstruction time per image and 43 db PSNR on the FPGA quantized configuration.","PeriodicalId":146990,"journal":{"name":"2021 10th International Conference on Modern Circuits and Systems Technologies (MOCAST)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130691877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-05DOI: 10.1109/MOCAST52088.2021.9493340
Christos C. Spandonidis, Giannopoulos Fotis, N. Galiatsatos, Reppas Dimitris, A. Petsa, D. Spyropoulos
Pipelines are one of the most common systems for storing and transporting petroleum products, both liquid and gaseous. Despite the durable structures, leakages can occur for many reasons, causing environmental disasters, energy waste, and, in some cases, human losses. The object of the ESTHISIS project is the development of a low-cost and low-energy wireless sensor system for the immediate detection of leaks in metallic piping systems for the transport of liquid and gaseous petroleum products in a noisy industrial environment. The method to be followed will be based on processing the changes monitored in the spectrum of vibration signals appearing in the pipeline walls due to a leakage effect and will aim at minimal interference in the piping system. It is intended to use low frequencies to detect and characterize leakage to increase the range of sensors and thus to reduce cost. In the current work, the smart sensor system developed for signal acquisition and data analysis is described. The work focuses on the hardware of the system and crucial details that enable the time synchronization of the system. Discussion on the main challenges faced as well as results of integration and lab-scale tests have been also included.
{"title":"Autonomous low-cost Wireless Sensor platform for Leakage Detection in Oil and Gas Pipes","authors":"Christos C. Spandonidis, Giannopoulos Fotis, N. Galiatsatos, Reppas Dimitris, A. Petsa, D. Spyropoulos","doi":"10.1109/MOCAST52088.2021.9493340","DOIUrl":"https://doi.org/10.1109/MOCAST52088.2021.9493340","url":null,"abstract":"Pipelines are one of the most common systems for storing and transporting petroleum products, both liquid and gaseous. Despite the durable structures, leakages can occur for many reasons, causing environmental disasters, energy waste, and, in some cases, human losses. The object of the ESTHISIS project is the development of a low-cost and low-energy wireless sensor system for the immediate detection of leaks in metallic piping systems for the transport of liquid and gaseous petroleum products in a noisy industrial environment. The method to be followed will be based on processing the changes monitored in the spectrum of vibration signals appearing in the pipeline walls due to a leakage effect and will aim at minimal interference in the piping system. It is intended to use low frequencies to detect and characterize leakage to increase the range of sensors and thus to reduce cost. In the current work, the smart sensor system developed for signal acquisition and data analysis is described. The work focuses on the hardware of the system and crucial details that enable the time synchronization of the system. Discussion on the main challenges faced as well as results of integration and lab-scale tests have been also included.","PeriodicalId":146990,"journal":{"name":"2021 10th International Conference on Modern Circuits and Systems Technologies (MOCAST)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129899230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-05DOI: 10.1109/MOCAST52088.2021.9493346
Nick Rigogiannis, A. Boubaris, Zoi Agorastou, N. Papanikolaou, S. Siskos, E. Koutroulis
This paper focuses on the design of a low-voltage power converter for an on-chip PV cell-level inverter. Various topologies are discussed for the DC/DC stage, whereas the ZVS quasi-resonant boost and the synchronous boost are considered the most appropriate for this application. Both the aforementioned topologies are modeled and evaluated in terms of efficiency, by the aid of PSpice simulations. Due to requirements and limitations of the available 0.18 μm CMOS process technology, the synchronous boost is finally chosen as the most appropriate solution. As for the DC/AC stage, the H-bridge inverter configuration is selected, as a simple, compact and cost-effective solution. A prototype converter is designed and constructed with discrete components, so as to validate the functionality and performance of the proposed system. Finally, experimental results are presented, indicating the high efficiency that can be achieved.
{"title":"Experimental Study of a Low-Voltage PV Cell-Level DC/AC Converter","authors":"Nick Rigogiannis, A. Boubaris, Zoi Agorastou, N. Papanikolaou, S. Siskos, E. Koutroulis","doi":"10.1109/MOCAST52088.2021.9493346","DOIUrl":"https://doi.org/10.1109/MOCAST52088.2021.9493346","url":null,"abstract":"This paper focuses on the design of a low-voltage power converter for an on-chip PV cell-level inverter. Various topologies are discussed for the DC/DC stage, whereas the ZVS quasi-resonant boost and the synchronous boost are considered the most appropriate for this application. Both the aforementioned topologies are modeled and evaluated in terms of efficiency, by the aid of PSpice simulations. Due to requirements and limitations of the available 0.18 μm CMOS process technology, the synchronous boost is finally chosen as the most appropriate solution. As for the DC/AC stage, the H-bridge inverter configuration is selected, as a simple, compact and cost-effective solution. A prototype converter is designed and constructed with discrete components, so as to validate the functionality and performance of the proposed system. Finally, experimental results are presented, indicating the high efficiency that can be achieved.","PeriodicalId":146990,"journal":{"name":"2021 10th International Conference on Modern Circuits and Systems Technologies (MOCAST)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133882664","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-05DOI: 10.1109/MOCAST52088.2021.9493399
Alaa AbdAlRahman, A. M. Abdelaty, A. Soltan, A. Radwan
Fractional calculus increases the flexibility of a system by studying the unexplored space between two integers. However, fractional calculus’s main challenge is its implementation due to its memory dependency, which appears in the amplitudes of the w coefficients in Grunwald–Letnikov(GL) definition. A modified GL approximation is proposed to control this dependency and decrease the error. The suggested approximation is based on the difference of the w binomial coefficients, which makes the new coefficients amplitudes decay faster. Three methods are discussed and compared for implementing the standard and the proposed GL approximation. The modified approximation shows an improvement, especially in the integration region of − 1 < α < −0.5. For example, the modified approximation results in an average absolute error of (0.1987) while the standard approximation results in an average absolute error of (0.8636) for sin(t) signal at α = −0.95, step size (h) of 0.01, window size of 64, and number of samples of 6283.
{"title":"An Improved Approximation of Grunwald-Letnikov Fractional Integral","authors":"Alaa AbdAlRahman, A. M. Abdelaty, A. Soltan, A. Radwan","doi":"10.1109/MOCAST52088.2021.9493399","DOIUrl":"https://doi.org/10.1109/MOCAST52088.2021.9493399","url":null,"abstract":"Fractional calculus increases the flexibility of a system by studying the unexplored space between two integers. However, fractional calculus’s main challenge is its implementation due to its memory dependency, which appears in the amplitudes of the w coefficients in Grunwald–Letnikov(GL) definition. A modified GL approximation is proposed to control this dependency and decrease the error. The suggested approximation is based on the difference of the w binomial coefficients, which makes the new coefficients amplitudes decay faster. Three methods are discussed and compared for implementing the standard and the proposed GL approximation. The modified approximation shows an improvement, especially in the integration region of − 1 < α < −0.5. For example, the modified approximation results in an average absolute error of (0.1987) while the standard approximation results in an average absolute error of (0.8636) for sin(t) signal at α = −0.95, step size (h) of 0.01, window size of 64, and number of samples of 6283.","PeriodicalId":146990,"journal":{"name":"2021 10th International Conference on Modern Circuits and Systems Technologies (MOCAST)","volume":"239 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134268702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-05DOI: 10.1109/MOCAST52088.2021.9493402
A. Polo, H. Ahmadi, S. Goudos, Junqiang Hu, Jin Huang, Moman Khan, Baozhu Li, Maokun Li, G. Oliveri, P. Rocca, M. Salucci, Fan Yang, Shiwen Yang, A. Massa
An entire long-term educational framework has been designed and implemented by the ELEDIA Research Center to (i) renew the way of teaching electromagnetics (EM) and modern communication systems to future engineers and (ii) increase students’ self-confidence and admiration of the applicative and technological aspects of Maxwell’s equations. According to authors’ expectations and students’ feedback, such a training ecosystem will help a computer-naive generation in developing a more natural engineer-oriented thinking mechanism and attitude for continuously adapting to technological advances in EM leading-edge research and industry.
{"title":"Advanced Teaching in Electromagnetics at the ELEDIA Research Center","authors":"A. Polo, H. Ahmadi, S. Goudos, Junqiang Hu, Jin Huang, Moman Khan, Baozhu Li, Maokun Li, G. Oliveri, P. Rocca, M. Salucci, Fan Yang, Shiwen Yang, A. Massa","doi":"10.1109/MOCAST52088.2021.9493402","DOIUrl":"https://doi.org/10.1109/MOCAST52088.2021.9493402","url":null,"abstract":"An entire long-term educational framework has been designed and implemented by the ELEDIA Research Center to (i) renew the way of teaching electromagnetics (EM) and modern communication systems to future engineers and (ii) increase students’ self-confidence and admiration of the applicative and technological aspects of Maxwell’s equations. According to authors’ expectations and students’ feedback, such a training ecosystem will help a computer-naive generation in developing a more natural engineer-oriented thinking mechanism and attitude for continuously adapting to technological advances in EM leading-edge research and industry.","PeriodicalId":146990,"journal":{"name":"2021 10th International Conference on Modern Circuits and Systems Technologies (MOCAST)","volume":"209 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114286907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-05DOI: 10.1109/MOCAST52088.2021.9493335
Savvas Chalkidis, E. Vassos, A. Boursianis, A. Feresidis, S. Goudos
Intelligent reflection surfaces (IRS) facilitate wireless environments by increasing spectrum and energy efficiencies. IRS will be considered a key element in 5G and Beyond cellular networks. IRS design is based on the unit cells. In this paper, we present the design of unit cells based on transparent materials at millimetre-wave frequencies. The transparency of the surface is achieved by using materials such as Indium tin oxide (ITO) and quartz. Simulations have been carried out using CST microwave studio to evaluate the reflection characteristics of the proposed unit cells. Simulations suggest a maximum shift in the reflection phase up to 336° for variation in the dimensions of the unit cell with low reflection losses at 60GHz for 5G and Beyond Wireless Networks.
{"title":"Design of Unit Cells for Intelligent Reflection Surfaces Based on Transparent Materials","authors":"Savvas Chalkidis, E. Vassos, A. Boursianis, A. Feresidis, S. Goudos","doi":"10.1109/MOCAST52088.2021.9493335","DOIUrl":"https://doi.org/10.1109/MOCAST52088.2021.9493335","url":null,"abstract":"Intelligent reflection surfaces (IRS) facilitate wireless environments by increasing spectrum and energy efficiencies. IRS will be considered a key element in 5G and Beyond cellular networks. IRS design is based on the unit cells. In this paper, we present the design of unit cells based on transparent materials at millimetre-wave frequencies. The transparency of the surface is achieved by using materials such as Indium tin oxide (ITO) and quartz. Simulations have been carried out using CST microwave studio to evaluate the reflection characteristics of the proposed unit cells. Simulations suggest a maximum shift in the reflection phase up to 336° for variation in the dimensions of the unit cell with low reflection losses at 60GHz for 5G and Beyond Wireless Networks.","PeriodicalId":146990,"journal":{"name":"2021 10th International Conference on Modern Circuits and Systems Technologies (MOCAST)","volume":"380 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115477277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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