Pub Date : 2020-01-01DOI: 10.1109/Confluence47617.2020.9058211
Shruti Gupta, A. Rana, Vineet Kansal
In the current scenario, heuristic approaches are broadly used in research in interdisciplinary categories. Heuristic Algorithms are used to get better and optimized results. the limitations are occur when we have to do selective and situational use of the algorithms amongst the all. In this paper we compared the results of Genetic Algorithm, Harmony Search and Firefly Algorithm on one of the popular problem Travelling Salesman problem(TSP). On TSP we proposed our own algorithm for the optimized cost of length of the tour.
{"title":"Comparison of Heuristic techniques:A case of TSP","authors":"Shruti Gupta, A. Rana, Vineet Kansal","doi":"10.1109/Confluence47617.2020.9058211","DOIUrl":"https://doi.org/10.1109/Confluence47617.2020.9058211","url":null,"abstract":"In the current scenario, heuristic approaches are broadly used in research in interdisciplinary categories. Heuristic Algorithms are used to get better and optimized results. the limitations are occur when we have to do selective and situational use of the algorithms amongst the all. In this paper we compared the results of Genetic Algorithm, Harmony Search and Firefly Algorithm on one of the popular problem Travelling Salesman problem(TSP). On TSP we proposed our own algorithm for the optimized cost of length of the tour.","PeriodicalId":180005,"journal":{"name":"2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116352872","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 : 2020-01-01DOI: 10.1109/Confluence47617.2020.9058219
Stamatios-Aggelos N. Alexandropoulos, S. Kotsiantis, Violetta E. Piperigou, M. Vrahatis
A vast number of factors influence the applicability of machine learning methods and the use of statistical models for a given task. The existence of outliers in a data set is a common issue that needs to be tackled. The identification of such values is a difficult, yet very useful project. In many cases errors or dissimilar values to the majority of the data are useless. Nevertheless, valuable information can be hidden in outliers’ set. During the last years, although several models have been developed for outlier detection, there is always space for new, intelligent, more efficient and less time consuming techniques for this issue. In the present work we provide a new ensemble method for outlier detection. In order to test the proposed methodology, comparisons are made with widely used techniques for outlier detection. The results obtained indicate that our model is robust and quite competitive to the other methods.
{"title":"A new ensemble method for outlier identification","authors":"Stamatios-Aggelos N. Alexandropoulos, S. Kotsiantis, Violetta E. Piperigou, M. Vrahatis","doi":"10.1109/Confluence47617.2020.9058219","DOIUrl":"https://doi.org/10.1109/Confluence47617.2020.9058219","url":null,"abstract":"A vast number of factors influence the applicability of machine learning methods and the use of statistical models for a given task. The existence of outliers in a data set is a common issue that needs to be tackled. The identification of such values is a difficult, yet very useful project. In many cases errors or dissimilar values to the majority of the data are useless. Nevertheless, valuable information can be hidden in outliers’ set. During the last years, although several models have been developed for outlier detection, there is always space for new, intelligent, more efficient and less time consuming techniques for this issue. In the present work we provide a new ensemble method for outlier detection. In order to test the proposed methodology, comparisons are made with widely used techniques for outlier detection. The results obtained indicate that our model is robust and quite competitive to the other methods.","PeriodicalId":180005,"journal":{"name":"2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124687089","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 : 2020-01-01DOI: 10.1109/Confluence47617.2020.9058120
Ayushi Grover, Anukriti Kalani, S. Dubey
Healthcare is a human right and in this complex technology driven world, healthcare industry is equipped with modern technology for the solution of disease but struggles when it comes to prevent them beforehand. Machine learning can transform healthcare industry. Machine Learning provides a wide scope of apparatuses, strategies and structures to address difficulties like electronic record the executives, information combination, PC supported judgments and disease expectation. This research paper aims to predict disease accurately according to the symptoms of patients and helps doctor in better diagnosis, further reducing the cost of treatment and improving quality of life. It includes the comparative study of the outcomes and time required for analysis and prediction of disease by various machine learning algorithms and contribute towards research in healthcare department.
{"title":"Analytical Approach towards Prediction of Diseases Using Machine Learning Algorithms","authors":"Ayushi Grover, Anukriti Kalani, S. Dubey","doi":"10.1109/Confluence47617.2020.9058120","DOIUrl":"https://doi.org/10.1109/Confluence47617.2020.9058120","url":null,"abstract":"Healthcare is a human right and in this complex technology driven world, healthcare industry is equipped with modern technology for the solution of disease but struggles when it comes to prevent them beforehand. Machine learning can transform healthcare industry. Machine Learning provides a wide scope of apparatuses, strategies and structures to address difficulties like electronic record the executives, information combination, PC supported judgments and disease expectation. This research paper aims to predict disease accurately according to the symptoms of patients and helps doctor in better diagnosis, further reducing the cost of treatment and improving quality of life. It includes the comparative study of the outcomes and time required for analysis and prediction of disease by various machine learning algorithms and contribute towards research in healthcare department.","PeriodicalId":180005,"journal":{"name":"2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128343234","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 : 2020-01-01DOI: 10.1109/Confluence47617.2020.9058308
Megha Kasera, R. Johari
A social structure constituting a set of nodes, representing social actors and edges or lines representing relation between these nodes or actors is a social network. Social network plays a vital role in circulation of information and innovation leading to analysis of the network and attracted attention in research field. The analysis of social network as a whole means, representation of all its actors and structure present in that social network forming part of a community. Community detection aims to divide the network into dense areas of graph. The dense regions usually correlates to entities which are familiar to each other, and form part of a community. Similar tastes and desires of the members in a community, enables exchange of information amongst various communities. Network science is the study of complex networks. There are various models defined in network science. Erdős–Rényi random graph model, Configuration model, Watts–Strogatz small world model, Barabási–Albert (BA) preferential attachment model, Mediation-driven attachment model, Fitness model are the various network science models. The current research work consists of application of these models on real world data and comparison between the final output with the use of R Studio.
{"title":"Identification and Implementation of Network Science Models for Centrality Measure using Social Network Analysis","authors":"Megha Kasera, R. Johari","doi":"10.1109/Confluence47617.2020.9058308","DOIUrl":"https://doi.org/10.1109/Confluence47617.2020.9058308","url":null,"abstract":"A social structure constituting a set of nodes, representing social actors and edges or lines representing relation between these nodes or actors is a social network. Social network plays a vital role in circulation of information and innovation leading to analysis of the network and attracted attention in research field. The analysis of social network as a whole means, representation of all its actors and structure present in that social network forming part of a community. Community detection aims to divide the network into dense areas of graph. The dense regions usually correlates to entities which are familiar to each other, and form part of a community. Similar tastes and desires of the members in a community, enables exchange of information amongst various communities. Network science is the study of complex networks. There are various models defined in network science. Erdős–Rényi random graph model, Configuration model, Watts–Strogatz small world model, Barabási–Albert (BA) preferential attachment model, Mediation-driven attachment model, Fitness model are the various network science models. The current research work consists of application of these models on real world data and comparison between the final output with the use of R Studio.","PeriodicalId":180005,"journal":{"name":"2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127378102","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 : 2020-01-01DOI: 10.1109/Confluence47617.2020.9058201
D. P. Singh, Manish Sharma
A 2×2 MIMO antenna with high isolation and designed on microwave substrate with permittivity 2.65 is reported with exclusion of dual notched band characteristics WiMAX, WLAN). Radiating antenna elements are placed perpendicular to each other without using any isolation technique. Designed antenna is etched with two circular slots with gap gi & g2 providing removal of interfering bands. Diversity performance of antenna is also studied including ECC and TARC. Designed antenna offers dipole like pattern and omni-directional pattern in H-plane which indicates that designed antenna can be used in either plane for different wireless applications.
{"title":"A UWB MIMO Antenna With Circular Ring Slotted Dual Notched Band High Isolation Between Two Input Ports For Wireless Network Applications","authors":"D. P. Singh, Manish Sharma","doi":"10.1109/Confluence47617.2020.9058201","DOIUrl":"https://doi.org/10.1109/Confluence47617.2020.9058201","url":null,"abstract":"A 2×2 MIMO antenna with high isolation and designed on microwave substrate with permittivity 2.65 is reported with exclusion of dual notched band characteristics WiMAX, WLAN). Radiating antenna elements are placed perpendicular to each other without using any isolation technique. Designed antenna is etched with two circular slots with gap gi & g2 providing removal of interfering bands. Diversity performance of antenna is also studied including ECC and TARC. Designed antenna offers dipole like pattern and omni-directional pattern in H-plane which indicates that designed antenna can be used in either plane for different wireless applications.","PeriodicalId":180005,"journal":{"name":"2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128938117","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 : 2020-01-01DOI: 10.1109/Confluence47617.2020.9057983
A. Gupta, Debangsi Satapathy, Sanjeev Thakur
Farming, all around the world is considered as one of the largest agro-sector which is set as a leading production to economic development for a country. Every person irrespective of occupation they seek, are dependent on food consumption for their survival. Scientists and researchers are trying to turn up the agricultural sector into a field that is cost-efficient, with enhanced equipment’s keeping in mind the optimum utilization of resources. Thus, technologies like Smart Farming and Internet of Things, makes it quite easy to handle and monitor with added up concepts like Machine Learning algorithms and Sensors which allow analyzing the processes to work in ease. The paper focuses on a technology based solution to be proposed for cultivation of specific (Tomato) plant using the above mentioned techniques to enhance the yielding properties by following three different approaches (as explained in Section VI).
{"title":"Technology based Streamlined Agro-Farming Techniques","authors":"A. Gupta, Debangsi Satapathy, Sanjeev Thakur","doi":"10.1109/Confluence47617.2020.9057983","DOIUrl":"https://doi.org/10.1109/Confluence47617.2020.9057983","url":null,"abstract":"Farming, all around the world is considered as one of the largest agro-sector which is set as a leading production to economic development for a country. Every person irrespective of occupation they seek, are dependent on food consumption for their survival. Scientists and researchers are trying to turn up the agricultural sector into a field that is cost-efficient, with enhanced equipment’s keeping in mind the optimum utilization of resources. Thus, technologies like Smart Farming and Internet of Things, makes it quite easy to handle and monitor with added up concepts like Machine Learning algorithms and Sensors which allow analyzing the processes to work in ease. The paper focuses on a technology based solution to be proposed for cultivation of specific (Tomato) plant using the above mentioned techniques to enhance the yielding properties by following three different approaches (as explained in Section VI).","PeriodicalId":180005,"journal":{"name":"2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130481830","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 : 2020-01-01DOI: 10.1109/Confluence47617.2020.9057926
Ankul Sharma
Smartphones are playing a major role in delivering effective solutions to the day-to-day problems of our society. Smartphones have smart applications that encompasses a whole range of domains ranging from the online payments systems such as (Paytm, Phonepe, BHIM etc) to the food delivery systems such as (Zomato, Swiggy, Uber eats etc). In this paper, we have proposed and designed a cloud-based smart-phone application “Mission Swachhta” that focuses on delivering a clean society. The main aim of this application is to bridge the gap between the end-users (people) and the authorities to attain a clean environment. This paper covers both the system and hardware requirements of this application. Also, it briefs about the functionalities of each components and inter-components interactions. The supposed target audience for this report includes capacity traders and technical designers. Additionally, even though the meant target market of this record isn't the ultimate client, its miles intended to be readable through a typical Mission Swachhta app person. This report will not only give the software and hardware requirements for the functioning of the software however will even give a detailed view of the interrelation and interaction of the consumer with the software and the way to efficaciously enforce the cloud for record garage and infrastructure. The consumer can speak with the desired authority in addition to can register his grievances and dutiful movement is taken at the registered grievance.
{"title":"Mission Swachhta : Mobile application based on Mobile Cloud Computing","authors":"Ankul Sharma","doi":"10.1109/Confluence47617.2020.9057926","DOIUrl":"https://doi.org/10.1109/Confluence47617.2020.9057926","url":null,"abstract":"Smartphones are playing a major role in delivering effective solutions to the day-to-day problems of our society. Smartphones have smart applications that encompasses a whole range of domains ranging from the online payments systems such as (Paytm, Phonepe, BHIM etc) to the food delivery systems such as (Zomato, Swiggy, Uber eats etc). In this paper, we have proposed and designed a cloud-based smart-phone application “Mission Swachhta” that focuses on delivering a clean society. The main aim of this application is to bridge the gap between the end-users (people) and the authorities to attain a clean environment. This paper covers both the system and hardware requirements of this application. Also, it briefs about the functionalities of each components and inter-components interactions. The supposed target audience for this report includes capacity traders and technical designers. Additionally, even though the meant target market of this record isn't the ultimate client, its miles intended to be readable through a typical Mission Swachhta app person. This report will not only give the software and hardware requirements for the functioning of the software however will even give a detailed view of the interrelation and interaction of the consumer with the software and the way to efficaciously enforce the cloud for record garage and infrastructure. The consumer can speak with the desired authority in addition to can register his grievances and dutiful movement is taken at the registered grievance.","PeriodicalId":180005,"journal":{"name":"2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128779919","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 : 2020-01-01DOI: 10.1109/Confluence47617.2020.9058087
Utkarsh Saxena, J. Sodhi, Yaduveer Singh
A Distributed Denial of Service (DDoS) attack is an attack which compromised the bandwidth of the whole network by choking down all the available network resources which are publicly available, thus makes the access of that resource unavailable. The DDoS attack is more vulnerable than a normal Dos attack because here the sources of attack origin are more than one, so users cannot even estimate how to detect and where to take actions so that attacks can be dissolved. DDoS attacks in Smart home could be more severe because in a smart home network the embedded operating system is open and can be easily compromised plus there is always a risk associated with the authentication mechanism in a smart. So, there is a need for a proper mechanism as well as a suitable approach so that a DDoS attack can be mitigated. This Paper suggests that the remedy that must be taken in order to counter-affect the DDoS attack in a smart home network.
{"title":"An Analysis of DDoS Attacks in a Smart Home Networks","authors":"Utkarsh Saxena, J. Sodhi, Yaduveer Singh","doi":"10.1109/Confluence47617.2020.9058087","DOIUrl":"https://doi.org/10.1109/Confluence47617.2020.9058087","url":null,"abstract":"A Distributed Denial of Service (DDoS) attack is an attack which compromised the bandwidth of the whole network by choking down all the available network resources which are publicly available, thus makes the access of that resource unavailable. The DDoS attack is more vulnerable than a normal Dos attack because here the sources of attack origin are more than one, so users cannot even estimate how to detect and where to take actions so that attacks can be dissolved. DDoS attacks in Smart home could be more severe because in a smart home network the embedded operating system is open and can be easily compromised plus there is always a risk associated with the authentication mechanism in a smart. So, there is a need for a proper mechanism as well as a suitable approach so that a DDoS attack can be mitigated. This Paper suggests that the remedy that must be taken in order to counter-affect the DDoS attack in a smart home network.","PeriodicalId":180005,"journal":{"name":"2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128834690","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 : 2020-01-01DOI: 10.1109/Confluence47617.2020.9057913
Rohit Kumar Kaliyar, K. Ram, Akansha Sharma, Smita Tiwari, N. Ahuja, Mohit Agrawal
Twitter is an online microblogging tool that has 400 million messages per day. SemEval-2018 Tasks have already been presented and explored in the previous years by the name of “Affect in Tweets” but the scope for improvement never ends. So, in this research paper, we come up with deep learning architecture which is extremely coherent for the given task of extracting emotion intensity and classes from tweets (description of the task is given on www.codalab.com for details). Deep learning models are productive due to their automatic learning capability and automatic feature extraction. This research paper highlights the implementation of deep learning-based models such as convolutional neural networks and LSTM for classifications. The implemented tasks are-:1. emotion intensity regression 2. Emotion intensity ordinal classification,z 3. Multilabel emotion classification. We have expressed that the fine-grained intensity scores that we have obtained are reliable. Our dataset is beneficial for testing supervised machine learning algorithms for multi-label classification, intensity regression, sleuthing ordinal category of intensity of feeling (low, moderate, etc.). We have implemented various machine learning and deep learning-based models and achieved an accuracy of 77.64% in E-oc (Emotion ordinal classification) task, which is the highest among all competitors.
{"title":"Affects in Tweets with Real Time Emotions using Deep Learning Techniques: A Novel Approach","authors":"Rohit Kumar Kaliyar, K. Ram, Akansha Sharma, Smita Tiwari, N. Ahuja, Mohit Agrawal","doi":"10.1109/Confluence47617.2020.9057913","DOIUrl":"https://doi.org/10.1109/Confluence47617.2020.9057913","url":null,"abstract":"Twitter is an online microblogging tool that has 400 million messages per day. SemEval-2018 Tasks have already been presented and explored in the previous years by the name of “Affect in Tweets” but the scope for improvement never ends. So, in this research paper, we come up with deep learning architecture which is extremely coherent for the given task of extracting emotion intensity and classes from tweets (description of the task is given on www.codalab.com for details). Deep learning models are productive due to their automatic learning capability and automatic feature extraction. This research paper highlights the implementation of deep learning-based models such as convolutional neural networks and LSTM for classifications. The implemented tasks are-:1. emotion intensity regression 2. Emotion intensity ordinal classification,z 3. Multilabel emotion classification. We have expressed that the fine-grained intensity scores that we have obtained are reliable. Our dataset is beneficial for testing supervised machine learning algorithms for multi-label classification, intensity regression, sleuthing ordinal category of intensity of feeling (low, moderate, etc.). We have implemented various machine learning and deep learning-based models and achieved an accuracy of 77.64% in E-oc (Emotion ordinal classification) task, which is the highest among all competitors.","PeriodicalId":180005,"journal":{"name":"2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126385633","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 : 2020-01-01DOI: 10.1109/Confluence47617.2020.9058021
Sarthak Seth, Dhruv C. Mathur
Advancements in mobile data communications require a very robust and reliable system. Future wireless systems requires high bit rate, low bit error rate, maximum transmission with very low power, lower bandwidth etc. The designed system should also be able to combat the effects of noise, co-channel interference (CCI), inter-symbol interference (ISI), spatial correlation and multipath fading effects. These effects deteriorate the performance of system significantly. MIMO system with more than one antenna at the transmitter and the receiver are used to combat all these impairments. Different detection techniques are applied at the receiver for the equalization and reduction of unwanted effects. In this paper, bit error rate (BER) of different equalization algorithms has been derived under the influence of ISI, CCI, and spatial correlation. Different Equalization techniques like ZF, MMSE, ZF-SIC, MMSE-SIC and ML.
{"title":"Performance Characterization of Equalization Techniques in MIMO System under Co-channel Interference and Spatial Correlation","authors":"Sarthak Seth, Dhruv C. Mathur","doi":"10.1109/Confluence47617.2020.9058021","DOIUrl":"https://doi.org/10.1109/Confluence47617.2020.9058021","url":null,"abstract":"Advancements in mobile data communications require a very robust and reliable system. Future wireless systems requires high bit rate, low bit error rate, maximum transmission with very low power, lower bandwidth etc. The designed system should also be able to combat the effects of noise, co-channel interference (CCI), inter-symbol interference (ISI), spatial correlation and multipath fading effects. These effects deteriorate the performance of system significantly. MIMO system with more than one antenna at the transmitter and the receiver are used to combat all these impairments. Different detection techniques are applied at the receiver for the equalization and reduction of unwanted effects. In this paper, bit error rate (BER) of different equalization algorithms has been derived under the influence of ISI, CCI, and spatial correlation. Different Equalization techniques like ZF, MMSE, ZF-SIC, MMSE-SIC and ML.","PeriodicalId":180005,"journal":{"name":"2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124908103","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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