Pub Date : 2022-02-16DOI: 10.1109/ICEEICT53079.2022.9768534
Aditi Awasthy
This work aims to build a Vedic Multiplier using the Indian Vedic Mathematics technique as the best alternative for multiplying algorithm. The performance of a high-speed CPU is heavily dependent on a component known as a multiplier. In this project, we will use the Vedic mathematics algorithm with detector and compressor circuits to overcome these major challenges of delay and complexity. We will focus on minimizing the processing delay of the digital circuit thereby increasing the speed. Also, reducing the switching activities, that will reduce the power consumption. The algorithm that we will use is ‘Urdhva-Tiryagbhyam Sutra’. Simulation will be done using Xilinx ISE platform with Verilog language. Finally, the goal of this study is to design an effective Vedic Multiplier employing the Urdhva-Tiryabhyam algorithm, followed by a comparison of the proposed and conventional multipliers based on area, propagation delay, and power, with improved performance factors.
{"title":"VLSI Implementation of Multiplier and Adder Circuits with Vedic Algorithm Computation","authors":"Aditi Awasthy","doi":"10.1109/ICEEICT53079.2022.9768534","DOIUrl":"https://doi.org/10.1109/ICEEICT53079.2022.9768534","url":null,"abstract":"This work aims to build a Vedic Multiplier using the Indian Vedic Mathematics technique as the best alternative for multiplying algorithm. The performance of a high-speed CPU is heavily dependent on a component known as a multiplier. In this project, we will use the Vedic mathematics algorithm with detector and compressor circuits to overcome these major challenges of delay and complexity. We will focus on minimizing the processing delay of the digital circuit thereby increasing the speed. Also, reducing the switching activities, that will reduce the power consumption. The algorithm that we will use is ‘Urdhva-Tiryagbhyam Sutra’. Simulation will be done using Xilinx ISE platform with Verilog language. Finally, the goal of this study is to design an effective Vedic Multiplier employing the Urdhva-Tiryabhyam algorithm, followed by a comparison of the proposed and conventional multipliers based on area, propagation delay, and power, with improved performance factors.","PeriodicalId":201910,"journal":{"name":"2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125200660","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 : 2022-02-16DOI: 10.1109/ICEEICT53079.2022.9768557
Piyush Kulshreshtha, A. Garg
The 5G Network provides higher bandwidth, low latency, low TCO and an ultra density network through use of several new technologies. However, these technologies also lead to a lot of vulnerabilities in the network and make it susceptible to security attacks by hackers. Detection of these attacks requires anomaly detection in network traffic which can be done quickly and efficiently through machine learning techniques. This review paper explores the use of several such supervised learning techniques for Intrusion Detection. A popular dataset _ KDD99, has been utilized to model and compare Intrusion Detection through a set of multi class classifiers. The dataset was cleaned and processed to remove the features that showed very high correlation with each other, The classifier used are Naïve Bayes, Decision Tree, Logistic Regression, Random Forest, Support Vector Machine and Gradient Boost. The paper also compares the performance of these classifiers for detecting abnormal traffic patterns in KDD99 dataset.
{"title":"Analysis of Machine Learning Approaches for Robust and Secure 5G Networks","authors":"Piyush Kulshreshtha, A. Garg","doi":"10.1109/ICEEICT53079.2022.9768557","DOIUrl":"https://doi.org/10.1109/ICEEICT53079.2022.9768557","url":null,"abstract":"The 5G Network provides higher bandwidth, low latency, low TCO and an ultra density network through use of several new technologies. However, these technologies also lead to a lot of vulnerabilities in the network and make it susceptible to security attacks by hackers. Detection of these attacks requires anomaly detection in network traffic which can be done quickly and efficiently through machine learning techniques. This review paper explores the use of several such supervised learning techniques for Intrusion Detection. A popular dataset _ KDD99, has been utilized to model and compare Intrusion Detection through a set of multi class classifiers. The dataset was cleaned and processed to remove the features that showed very high correlation with each other, The classifier used are Naïve Bayes, Decision Tree, Logistic Regression, Random Forest, Support Vector Machine and Gradient Boost. The paper also compares the performance of these classifiers for detecting abnormal traffic patterns in KDD99 dataset.","PeriodicalId":201910,"journal":{"name":"2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124108436","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 : 2022-02-16DOI: 10.1109/ICEEICT53079.2022.9768448
A. Vadivel, N. Moogambigai, S. Tamilselvan, P. Thangaraja
The major purpose of this study is to develop a methodical strategy for selecting appropriate qualities and options for neutrosophic score functions in a material selection problem of civil engineering utilising neutrosophic topology for decision-making problems.
{"title":"Application of Neutrosophic Sets Based on Neutrosophic Score Function in Material Selection","authors":"A. Vadivel, N. Moogambigai, S. Tamilselvan, P. Thangaraja","doi":"10.1109/ICEEICT53079.2022.9768448","DOIUrl":"https://doi.org/10.1109/ICEEICT53079.2022.9768448","url":null,"abstract":"The major purpose of this study is to develop a methodical strategy for selecting appropriate qualities and options for neutrosophic score functions in a material selection problem of civil engineering utilising neutrosophic topology for decision-making problems.","PeriodicalId":201910,"journal":{"name":"2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124179428","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 : 2022-02-16DOI: 10.1109/ICEEICT53079.2022.9768620
P. Thangaraj
In the literature, there have been several studies and introductions of fuzzy set extension and generalisation. A extension of the intuitionistic fuzzy set and fuzzy graph is the neutrosophic support digraph. The neutrosophic support graph is referred to as neutrosophic support digraph in this study since several fundamental operations are redefined (in short NSDG). NSDG is discussed in terms of mathematical operations and relationships. We also developed a scoring function-based approach to solving the shortest route issue.
{"title":"A New Network shortest path algorithm via Neutrosophic support digraph","authors":"P. Thangaraj","doi":"10.1109/ICEEICT53079.2022.9768620","DOIUrl":"https://doi.org/10.1109/ICEEICT53079.2022.9768620","url":null,"abstract":"In the literature, there have been several studies and introductions of fuzzy set extension and generalisation. A extension of the intuitionistic fuzzy set and fuzzy graph is the neutrosophic support digraph. The neutrosophic support graph is referred to as neutrosophic support digraph in this study since several fundamental operations are redefined (in short NSDG). NSDG is discussed in terms of mathematical operations and relationships. We also developed a scoring function-based approach to solving the shortest route issue.","PeriodicalId":201910,"journal":{"name":"2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"165 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127195999","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 : 2022-02-16DOI: 10.1109/ICEEICT53079.2022.9768560
Swati Thimmapuram, M. Laxmaiah, M. Sreelatha
Cognitive radio Network (CRN) is an intelligent technology and it periodically monitor unused licensed spectrum in a specific frequency band. The main issues with spectrum sensing in CRNs are the hidden terminal problem, which occurs during cognitive radio shading, severe multi-path faded or in buildings with high infiltration loss, while operating near a primary user (PU). Due to the hidden terminal problem, a cognitive radio (CR) can have failed to notice the PU's presence. Then access the unlicensed channel, cause interference in the license scheme, while this interference occurs in the system the probability errors will occurs in the network and reduces the spectrum utility. To overcome these issues, Quick Cooperative Spectrum Sensing (CSS) optimization framework in CRN (CSS-CRN) based on a May Fly optimization (MFO) and Gradient Descent Optimization (GDO) algorithm is proposed in this paper. Here, the weight vectors of CSS-CRN are optimized utilizing the hybrid heuristic Search based optimization algorithm namely May Fly optimization (MFO) and Gradient Descent Optimization (GDO) algorithm. Finally these weight vectors are used in the data fusion centre to assign spectrum in secondary users (SUs).
{"title":"Cooperative Spectrum Sensing Optimization in Cognitive Radio networks based on a Hybrid (MFO-GDO) Heuristic Search Algorithm","authors":"Swati Thimmapuram, M. Laxmaiah, M. Sreelatha","doi":"10.1109/ICEEICT53079.2022.9768560","DOIUrl":"https://doi.org/10.1109/ICEEICT53079.2022.9768560","url":null,"abstract":"Cognitive radio Network (CRN) is an intelligent technology and it periodically monitor unused licensed spectrum in a specific frequency band. The main issues with spectrum sensing in CRNs are the hidden terminal problem, which occurs during cognitive radio shading, severe multi-path faded or in buildings with high infiltration loss, while operating near a primary user (PU). Due to the hidden terminal problem, a cognitive radio (CR) can have failed to notice the PU's presence. Then access the unlicensed channel, cause interference in the license scheme, while this interference occurs in the system the probability errors will occurs in the network and reduces the spectrum utility. To overcome these issues, Quick Cooperative Spectrum Sensing (CSS) optimization framework in CRN (CSS-CRN) based on a May Fly optimization (MFO) and Gradient Descent Optimization (GDO) algorithm is proposed in this paper. Here, the weight vectors of CSS-CRN are optimized utilizing the hybrid heuristic Search based optimization algorithm namely May Fly optimization (MFO) and Gradient Descent Optimization (GDO) algorithm. Finally these weight vectors are used in the data fusion centre to assign spectrum in secondary users (SUs).","PeriodicalId":201910,"journal":{"name":"2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129454101","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 : 2022-02-16DOI: 10.1109/ICEEICT53079.2022.9768547
P. Lavanya, S. Ch, P. S
From the last decade, there has been expeditious growth and a worldwide success is perceived in the area of wireless ad-hoc networking. Especially, one class of wireless ad-hoc networks, that is, mobile ad-hoc network (MANET) drawing a great attention from the critical applications like emergency search and rescue operations and disaster recovery services. A MANET consists of mobile nodes that are capable of self-configuring the network instantly. However, the MANETs, containing wireless mobile ad-hoc nodes that are connected by multi-hop communication process, make routing the data packets in them a challenging task. In this paper, the essentials of unicast and multicast routing in mobile ad-hoc environments are focused. Moreover, the working principles of four eminent routing protocols such as DSDV, OLSR, DSR, and AODV have been presented in detail.
{"title":"Routing in Mobile Ad-hoc Networks - A Comprehensive Research","authors":"P. Lavanya, S. Ch, P. S","doi":"10.1109/ICEEICT53079.2022.9768547","DOIUrl":"https://doi.org/10.1109/ICEEICT53079.2022.9768547","url":null,"abstract":"From the last decade, there has been expeditious growth and a worldwide success is perceived in the area of wireless ad-hoc networking. Especially, one class of wireless ad-hoc networks, that is, mobile ad-hoc network (MANET) drawing a great attention from the critical applications like emergency search and rescue operations and disaster recovery services. A MANET consists of mobile nodes that are capable of self-configuring the network instantly. However, the MANETs, containing wireless mobile ad-hoc nodes that are connected by multi-hop communication process, make routing the data packets in them a challenging task. In this paper, the essentials of unicast and multicast routing in mobile ad-hoc environments are focused. Moreover, the working principles of four eminent routing protocols such as DSDV, OLSR, DSR, and AODV have been presented in detail.","PeriodicalId":201910,"journal":{"name":"2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126257838","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 : 2022-02-16DOI: 10.1109/ICEEICT53079.2022.9768571
T. Ravi, Malladi Kaushik, M. Sugadev, Chandu Pavan, Vinoth Manoharan
Introduction of cellular mobile communications have made a revolution in human life style and has been making life better and year by year by incorporating as much features as possible in the portable device. The key to addressing the demands of this high-end technologies, is to allow communication in the higher spectrum as suggested in the 5G telecommunications standard. Most experts predict the 5G work at the frequency of 28GHz as that of the contender because of its frequency band allocation. This technologies offers a broad variety of benefits, such as it delivers increased data rates and high-quality web - based applications, i.e., Audio, Live feed, and internet access. Moreover, these systems have highly proficient. Wireless antennas with a compact design and a wide bandwidth are in high demand. This method necessitates the use of a high-bandwidth antenna. There are various antennas present: the linear fractal the impedance matching array antenna features a reasonable design, a broader operating frequency range and relatively inexpensive fabrication cost because of the microstrip structure. A fractal is a self-generated object that recursively has a fractional dimension. In addition to that, they don't have any character size and also constructed many of themselves at different scales. Our paper emphasizes the design of a linear fractal impedance array antenna for matching the high gain and bandwidth requirements of 5G communication system. frequency of the antenna. Furthermore, the designed arrays are analyzed by fractal electrodynamics and simulated by HFSS (High-Frequency Structure Simulator) simulation software. The antenna is fabricated and analyzed with measured results.
{"title":"A Linear Fractal Impedance Matching Array Antenna for 5G Spectrum Applications","authors":"T. Ravi, Malladi Kaushik, M. Sugadev, Chandu Pavan, Vinoth Manoharan","doi":"10.1109/ICEEICT53079.2022.9768571","DOIUrl":"https://doi.org/10.1109/ICEEICT53079.2022.9768571","url":null,"abstract":"Introduction of cellular mobile communications have made a revolution in human life style and has been making life better and year by year by incorporating as much features as possible in the portable device. The key to addressing the demands of this high-end technologies, is to allow communication in the higher spectrum as suggested in the 5G telecommunications standard. Most experts predict the 5G work at the frequency of 28GHz as that of the contender because of its frequency band allocation. This technologies offers a broad variety of benefits, such as it delivers increased data rates and high-quality web - based applications, i.e., Audio, Live feed, and internet access. Moreover, these systems have highly proficient. Wireless antennas with a compact design and a wide bandwidth are in high demand. This method necessitates the use of a high-bandwidth antenna. There are various antennas present: the linear fractal the impedance matching array antenna features a reasonable design, a broader operating frequency range and relatively inexpensive fabrication cost because of the microstrip structure. A fractal is a self-generated object that recursively has a fractional dimension. In addition to that, they don't have any character size and also constructed many of themselves at different scales. Our paper emphasizes the design of a linear fractal impedance array antenna for matching the high gain and bandwidth requirements of 5G communication system. frequency of the antenna. Furthermore, the designed arrays are analyzed by fractal electrodynamics and simulated by HFSS (High-Frequency Structure Simulator) simulation software. The antenna is fabricated and analyzed with measured results.","PeriodicalId":201910,"journal":{"name":"2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126319138","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 : 2022-02-16DOI: 10.1109/ICEEICT53079.2022.9768478
Sanskruti Patel, Rachana Patel, Nilay Ganatra, S. Khant, Atul Patel
In the human body, kidney clears the waste from the body and maintains vigorous balance between salt, water, and minerals in human body. The misbalancing between these leads to disturbance of normal functions of human body. Chronic kidney disease is a condition presenting the damage occurred in the normal functioning of kidneys. Early detection of chronic kidney disease helps significantly preventing severe kidney damage. The advancements in information and communication technologies certainly improves health care services for individuals and societies. In recent years, artificial intelligence and machine learning have provided potential solution for solving complex problem in variety of sectors including health care. The aim of this study is to predict the choric kidney disease from the dataset taken from the UCI repository. The dataset contains 400 instances with 25 attributes including class variable. Four state-of-the-art supervised machine learning classifiers, i.e., XGBoost, decision tree, support vector machine, and K-Neighrest Neighbor are implemented and performance is evaluated. The result shows that the XGBoost classifier outperforms with 99% value for accuracy, 100% value for precision, 97% for recall and 98% value for F1-score. The study gives a direction to develop an automated computer-assisted system for chronic kidney disease prediction and diagnosis.
{"title":"An Experimental Study and Performance Analysis of Supervised Machine Learning Algorithms for Prognosis of Chronic Kidney Disease","authors":"Sanskruti Patel, Rachana Patel, Nilay Ganatra, S. Khant, Atul Patel","doi":"10.1109/ICEEICT53079.2022.9768478","DOIUrl":"https://doi.org/10.1109/ICEEICT53079.2022.9768478","url":null,"abstract":"In the human body, kidney clears the waste from the body and maintains vigorous balance between salt, water, and minerals in human body. The misbalancing between these leads to disturbance of normal functions of human body. Chronic kidney disease is a condition presenting the damage occurred in the normal functioning of kidneys. Early detection of chronic kidney disease helps significantly preventing severe kidney damage. The advancements in information and communication technologies certainly improves health care services for individuals and societies. In recent years, artificial intelligence and machine learning have provided potential solution for solving complex problem in variety of sectors including health care. The aim of this study is to predict the choric kidney disease from the dataset taken from the UCI repository. The dataset contains 400 instances with 25 attributes including class variable. Four state-of-the-art supervised machine learning classifiers, i.e., XGBoost, decision tree, support vector machine, and K-Neighrest Neighbor are implemented and performance is evaluated. The result shows that the XGBoost classifier outperforms with 99% value for accuracy, 100% value for precision, 97% for recall and 98% value for F1-score. The study gives a direction to develop an automated computer-assisted system for chronic kidney disease prediction and diagnosis.","PeriodicalId":201910,"journal":{"name":"2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127834847","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 : 2022-02-16DOI: 10.1109/ICEEICT53079.2022.9768446
G. K. J. Hussain, G. Manoj
Massive clients can use large-scale machine learning using federated learning without revealing their raw data to the outside world. It's capable of preserving client personal information while also achieving great learning performance for the client's benefit. Existing research on federated learning is primarily concerned with increasing learning efficiency and model accuracy. But in reality, customers are unwilling to take part in the learning process unless they are compensated for their time and effort consequently, it is critical to figure out how to get customers involved in federated learning by motivating them successfully. Other areas like crowdsourcing, cloud computing, smart grid, etc. are simpler than designing an incentive structure for federated learning. To begin, it's impossible to determine the exact worth of the training data collected from each individual client. Second, different federated learning algorithms' learning performance is challenging to model. This work examines the design of a federated learning incentive system. Before we evaluate and contrast different strategies, we provide taxonomy of existing federated learning incentive mechanisms. There have also been some innovative ideas for enticing customers to take part in federated learning.
{"title":"Federated Learning: A Survey of a New Approach to Machine Learning","authors":"G. K. J. Hussain, G. Manoj","doi":"10.1109/ICEEICT53079.2022.9768446","DOIUrl":"https://doi.org/10.1109/ICEEICT53079.2022.9768446","url":null,"abstract":"Massive clients can use large-scale machine learning using federated learning without revealing their raw data to the outside world. It's capable of preserving client personal information while also achieving great learning performance for the client's benefit. Existing research on federated learning is primarily concerned with increasing learning efficiency and model accuracy. But in reality, customers are unwilling to take part in the learning process unless they are compensated for their time and effort consequently, it is critical to figure out how to get customers involved in federated learning by motivating them successfully. Other areas like crowdsourcing, cloud computing, smart grid, etc. are simpler than designing an incentive structure for federated learning. To begin, it's impossible to determine the exact worth of the training data collected from each individual client. Second, different federated learning algorithms' learning performance is challenging to model. This work examines the design of a federated learning incentive system. Before we evaluate and contrast different strategies, we provide taxonomy of existing federated learning incentive mechanisms. There have also been some innovative ideas for enticing customers to take part in federated learning.","PeriodicalId":201910,"journal":{"name":"2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121489161","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 : 2022-02-16DOI: 10.1109/ICEEICT53079.2022.9768514
S. Gowthami, Puneet Kumar
In this work, a circularly polarized (CP) dual band corner extended slot antenna loaded with a split ring resonator (SRR), which is modified in its structure, is presented. The antenna operates in two bands. The lower resonance frequency is obtained due to the slot dimension. The slot antenna is excited using them microstrip feed line. The corner extended slot antenna produce two degenerative modes which are require to obtain CP in the lower resonant frequency. An SRR is etched on a corner of the slot structure to obtain the upper resonance frequency. The slot antenna produce magnetic field which is axial in direction to modified SRR and excites it. To achieve CP in the upper frequency band, strips with asymmetric in nature are introduced in the SRR which creates equal magnitude with a 90° phase. The CP antenna with dual band characteristics is capable of tuning the resonance frequencies and polarization sense independently in each frequency band. The designed antenna is operated at 1.58 GHz and 1.95 GHz. The simulated results shows that the lower resonant frequency has a −10 dB impedance bandwidth from 1.47GHz-1.62GHz and upper resonant frequency from 1.84 GHz-2.08 GHz. A 200MHz of axial ratio (<3dB) bandwidth in the lower resonant frequency and 130MHz in the upper resonant frequency is obtained respectively. The simulated radiation efficiency of >75% is achieved in both bands.
{"title":"Independently Tunable Dual Band Antenna loaded with modified Split Ring Resonator with Circular Polarization Characteristics for Wireless Applications","authors":"S. Gowthami, Puneet Kumar","doi":"10.1109/ICEEICT53079.2022.9768514","DOIUrl":"https://doi.org/10.1109/ICEEICT53079.2022.9768514","url":null,"abstract":"In this work, a circularly polarized (CP) dual band corner extended slot antenna loaded with a split ring resonator (SRR), which is modified in its structure, is presented. The antenna operates in two bands. The lower resonance frequency is obtained due to the slot dimension. The slot antenna is excited using them microstrip feed line. The corner extended slot antenna produce two degenerative modes which are require to obtain CP in the lower resonant frequency. An SRR is etched on a corner of the slot structure to obtain the upper resonance frequency. The slot antenna produce magnetic field which is axial in direction to modified SRR and excites it. To achieve CP in the upper frequency band, strips with asymmetric in nature are introduced in the SRR which creates equal magnitude with a 90° phase. The CP antenna with dual band characteristics is capable of tuning the resonance frequencies and polarization sense independently in each frequency band. The designed antenna is operated at 1.58 GHz and 1.95 GHz. The simulated results shows that the lower resonant frequency has a −10 dB impedance bandwidth from 1.47GHz-1.62GHz and upper resonant frequency from 1.84 GHz-2.08 GHz. A 200MHz of axial ratio (<3dB) bandwidth in the lower resonant frequency and 130MHz in the upper resonant frequency is obtained respectively. The simulated radiation efficiency of >75% is achieved in both bands.","PeriodicalId":201910,"journal":{"name":"2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"651 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121353344","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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