Pub Date : 2021-12-21DOI: 10.1109/NICS54270.2021.9701559
Giang Quynh Le Vu, Hung Tran, K. Truong
Pilot contamination is a major problem affecting the secrecy capacity of communication systems. The jammer is difficult to detect. This issue is also linked to numerous research projects. In this study, the authors propose a pilot attack detection method with a high detection probability and a reduced false-alarm probability in Massive MIMO Spatially-uncorrelated Rician Channels.
{"title":"Jammer Detection by Random Pilots in Massive MIMO Spatially-uncorrelated Rician Channels","authors":"Giang Quynh Le Vu, Hung Tran, K. Truong","doi":"10.1109/NICS54270.2021.9701559","DOIUrl":"https://doi.org/10.1109/NICS54270.2021.9701559","url":null,"abstract":"Pilot contamination is a major problem affecting the secrecy capacity of communication systems. The jammer is difficult to detect. This issue is also linked to numerous research projects. In this study, the authors propose a pilot attack detection method with a high detection probability and a reduced false-alarm probability in Massive MIMO Spatially-uncorrelated Rician Channels.","PeriodicalId":296963,"journal":{"name":"2021 8th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115985940","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 : 2021-12-21DOI: 10.1109/NICS54270.2021.9701513
Thanh-Hai Tran, Phuong Thi Tuyet Nguyen, Duc-Huy Tran, X. Manh, Danh H. Vu, Nguyen-Khang Ho, Khanh-Linh Do, Van-Tuan Nguyen, Long-Thuy Nguyen, V. Dao, Hai Vu
In this paper, we propose a framework that automatically classifies anatomical landmarks of Upper GastroIntestinal Endoscopy (UGIE). This framework aims to select the best deep neural network in terms of both criteria of classification performances and computational costs. We investigate two lightweight deep neural networks that are ResNet-18, MobileNet-V2 to learn hidden discriminant features for multi classification task. In addition, because convolutional neural networks (CNNs) are data hungry, we examine various data augmentation (DA) techniques such as Brightness and Contrast Transformation (BaC), Geometric Transformation (GeoT), and Variational Auto-Encoder (VAE). Impacts of these DA schemes are evaluated for both CNN models. The experiments are conducted on a self collected dataset of 3700 endoscopic images which contains 10 anatomical landmarks of UGIE. The results show outstanding performances of both models thanks to DA techniques compared to the original data usage. The best sensitivity is 97.43% and specificity is 99.71% using MobileNet-V2 with Geometric Transformation based DA technique at a frame-rate of 21fps. These results highlight the best model which has significant potential for developing computer-aided esophagogastroduodenoscopy (EGD) diagnostic systems.
{"title":"Classification of anatomical landmarks from upper gastrointestinal endoscopic images⋆","authors":"Thanh-Hai Tran, Phuong Thi Tuyet Nguyen, Duc-Huy Tran, X. Manh, Danh H. Vu, Nguyen-Khang Ho, Khanh-Linh Do, Van-Tuan Nguyen, Long-Thuy Nguyen, V. Dao, Hai Vu","doi":"10.1109/NICS54270.2021.9701513","DOIUrl":"https://doi.org/10.1109/NICS54270.2021.9701513","url":null,"abstract":"In this paper, we propose a framework that automatically classifies anatomical landmarks of Upper GastroIntestinal Endoscopy (UGIE). This framework aims to select the best deep neural network in terms of both criteria of classification performances and computational costs. We investigate two lightweight deep neural networks that are ResNet-18, MobileNet-V2 to learn hidden discriminant features for multi classification task. In addition, because convolutional neural networks (CNNs) are data hungry, we examine various data augmentation (DA) techniques such as Brightness and Contrast Transformation (BaC), Geometric Transformation (GeoT), and Variational Auto-Encoder (VAE). Impacts of these DA schemes are evaluated for both CNN models. The experiments are conducted on a self collected dataset of 3700 endoscopic images which contains 10 anatomical landmarks of UGIE. The results show outstanding performances of both models thanks to DA techniques compared to the original data usage. The best sensitivity is 97.43% and specificity is 99.71% using MobileNet-V2 with Geometric Transformation based DA technique at a frame-rate of 21fps. These results highlight the best model which has significant potential for developing computer-aided esophagogastroduodenoscopy (EGD) diagnostic systems.","PeriodicalId":296963,"journal":{"name":"2021 8th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122324446","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 : 2021-12-21DOI: 10.1109/NICS54270.2021.9701506
H. Vu, Ngoc-Dai Bui, Anh-Tu Nguyen, ThanhBangLe
The Quine-McCluskey method is an algorithm to minimize Boolean functions. Although the method can be programmed on computers, it takes a long time to return the set of prime implicants, thus slowing the analysis and design of digital logic circuits. As a result, it slows down the dynamic reconfiguration process of programmable logic devices. In this paper, we first propose a data representation for storing implicants in memory to reduce the cache misses of the program. We then propose an algorithm to find all prime implicants of a Boolean function. The algorithm aims to reuse the data available on cache, thus decreasing cache misses. After that, we propose an algorithm for step 2 of the Quine-McCluskey method to select the minimal number of essential prime implicants. The evaluation shows that our proposals achieve much higher performance than the original Quine-McCluskey method. The number of essential prime implicants is a low percentage, less than 50%, of the total prime implicants generated in step 1 of the method.
{"title":"Performance Evaluation of Quine-McCluskey Method on Multi-core CPU","authors":"H. Vu, Ngoc-Dai Bui, Anh-Tu Nguyen, ThanhBangLe","doi":"10.1109/NICS54270.2021.9701506","DOIUrl":"https://doi.org/10.1109/NICS54270.2021.9701506","url":null,"abstract":"The Quine-McCluskey method is an algorithm to minimize Boolean functions. Although the method can be programmed on computers, it takes a long time to return the set of prime implicants, thus slowing the analysis and design of digital logic circuits. As a result, it slows down the dynamic reconfiguration process of programmable logic devices. In this paper, we first propose a data representation for storing implicants in memory to reduce the cache misses of the program. We then propose an algorithm to find all prime implicants of a Boolean function. The algorithm aims to reuse the data available on cache, thus decreasing cache misses. After that, we propose an algorithm for step 2 of the Quine-McCluskey method to select the minimal number of essential prime implicants. The evaluation shows that our proposals achieve much higher performance than the original Quine-McCluskey method. The number of essential prime implicants is a low percentage, less than 50%, of the total prime implicants generated in step 1 of the method.","PeriodicalId":296963,"journal":{"name":"2021 8th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131763410","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 : 2021-12-21DOI: 10.1109/NICS54270.2021.9701563
Hien Do Hoang, Do Thi Thu Hien, Phan The Duy, Nghi Hoang Khoa, V. Pham
The rapid development of network technologies and the variety of user demands make it difficult for traditional network appliances to meet the requirements in deployment and operation. Different network designs can lead to a variety in equipment requirements. In a traditional network, besides the required cost for specialized hardware and software licenses of network appliances, it takes organizations to spend more time, financial cost, and effort to get the network deployed and operated. This task is even harder in the case of devices from various vendors, which need to be compatible with each other. Hence, in this paper, we propose an alternative solution using network function virtualization (NFV) to provide a more efficient network deploying and operating mechanism. NFVs have the same capability as network devices, they can be deployed individually or in a chain along with others. Moreover, service function chain (SFC) Orchestration is also our consideration for the time-effectiveness in deploying those NFV chains. Besides, the combination of SDN-based network and SFC is used to establish the connection between virtualized network functions and end devices. We also have a prototype implementation of the proposed architecture, and then perform evaluations on deployment time of service functions and accurate operations of deployed infrastructures. In addition, attack scenarios like DoS or Web attacks are performed to assess the protection capability of security-related NFVs.
{"title":"An Approach for Service Function Chain Orchestration in Combination with SDN-based Network","authors":"Hien Do Hoang, Do Thi Thu Hien, Phan The Duy, Nghi Hoang Khoa, V. Pham","doi":"10.1109/NICS54270.2021.9701563","DOIUrl":"https://doi.org/10.1109/NICS54270.2021.9701563","url":null,"abstract":"The rapid development of network technologies and the variety of user demands make it difficult for traditional network appliances to meet the requirements in deployment and operation. Different network designs can lead to a variety in equipment requirements. In a traditional network, besides the required cost for specialized hardware and software licenses of network appliances, it takes organizations to spend more time, financial cost, and effort to get the network deployed and operated. This task is even harder in the case of devices from various vendors, which need to be compatible with each other. Hence, in this paper, we propose an alternative solution using network function virtualization (NFV) to provide a more efficient network deploying and operating mechanism. NFVs have the same capability as network devices, they can be deployed individually or in a chain along with others. Moreover, service function chain (SFC) Orchestration is also our consideration for the time-effectiveness in deploying those NFV chains. Besides, the combination of SDN-based network and SFC is used to establish the connection between virtualized network functions and end devices. We also have a prototype implementation of the proposed architecture, and then perform evaluations on deployment time of service functions and accurate operations of deployed infrastructures. In addition, attack scenarios like DoS or Web attacks are performed to assess the protection capability of security-related NFVs.","PeriodicalId":296963,"journal":{"name":"2021 8th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127956948","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 : 2021-12-21DOI: 10.1109/NICS54270.2021.9701574
Gunawan
Prior studies have investigated community mobility to understand the spread of Covid-19 cases, especially during the early months. The goal of this study was to explain community mobility through social measures. Three composite measures, namely the social life satisfaction index, human development index, and ICT development index, were selected as social-related measures to explain community mobility. The data mining approach was adopted using the Knime Analytical Platform as the software and the Cross-Industry Standard Process for Data Mining as a process framework. The analysis covered the mobility fluctuation among 34 provinces in Indonesia using the data from Google Mobility Report from July 2020 to August 2021. Cluster analysis with the k-medoids algorithm grouped provinces into higher and lower mobility provinces. The findings indicated an association between mobility fluctuation among provinces and the social life satisfaction index, human development index, and ICT development index. Four provinces, namely Bali, Yogyakarta, Jakarta, and Riau Islands, had higher mobility, human development index, and ICT development index. The study provides evidence of factors explaining human mobility and thus enriches the literature on human mobility and the social impact of the Covid-19 pandemic. The finding also enhances the literature on applying data mining to social research at a country level. However, the generalization of this finding is limited as the analysis covers Indonesian data only. This study could be extended to other countries to arrive at more generalizable results across countries.
{"title":"Understanding Community Mobility through Life Satisfaction, Human Development, and ICT Development: a Data Mining Approach","authors":"Gunawan","doi":"10.1109/NICS54270.2021.9701574","DOIUrl":"https://doi.org/10.1109/NICS54270.2021.9701574","url":null,"abstract":"Prior studies have investigated community mobility to understand the spread of Covid-19 cases, especially during the early months. The goal of this study was to explain community mobility through social measures. Three composite measures, namely the social life satisfaction index, human development index, and ICT development index, were selected as social-related measures to explain community mobility. The data mining approach was adopted using the Knime Analytical Platform as the software and the Cross-Industry Standard Process for Data Mining as a process framework. The analysis covered the mobility fluctuation among 34 provinces in Indonesia using the data from Google Mobility Report from July 2020 to August 2021. Cluster analysis with the k-medoids algorithm grouped provinces into higher and lower mobility provinces. The findings indicated an association between mobility fluctuation among provinces and the social life satisfaction index, human development index, and ICT development index. Four provinces, namely Bali, Yogyakarta, Jakarta, and Riau Islands, had higher mobility, human development index, and ICT development index. The study provides evidence of factors explaining human mobility and thus enriches the literature on human mobility and the social impact of the Covid-19 pandemic. The finding also enhances the literature on applying data mining to social research at a country level. However, the generalization of this finding is limited as the analysis covers Indonesian data only. This study could be extended to other countries to arrive at more generalizable results across countries.","PeriodicalId":296963,"journal":{"name":"2021 8th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128792595","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}
Along with many solutions for determining the inverse parameter in pharmacokinetics, with this work, we propose two improved approaches to the original cluster Newton method. Applying Tikhonov regularization for hyperplane fitting in the CN method is the first method, and the efficient iterative process for the CN method is the next. When using these proposed approaches, it has been demonstrated that numerical experiments of both approaches can bring benefits such as saving iterations, reduced computation time, and clustering of points. They also move more stably and asymptotically with the diversity of solutions.
{"title":"Enhanced Approaches for Cluster Newton Method for Underdetermined Inverse Problems","authors":"Duong Tran Binh, Uyen Nguyen Duc, Tran Quang-Huy, Nguyen Thi Thu, Tran Duc Tan","doi":"10.1109/NICS54270.2021.9701550","DOIUrl":"https://doi.org/10.1109/NICS54270.2021.9701550","url":null,"abstract":"Along with many solutions for determining the inverse parameter in pharmacokinetics, with this work, we propose two improved approaches to the original cluster Newton method. Applying Tikhonov regularization for hyperplane fitting in the CN method is the first method, and the efficient iterative process for the CN method is the next. When using these proposed approaches, it has been demonstrated that numerical experiments of both approaches can bring benefits such as saving iterations, reduced computation time, and clustering of points. They also move more stably and asymptotically with the diversity of solutions.","PeriodicalId":296963,"journal":{"name":"2021 8th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"125 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120830396","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 : 2021-12-21DOI: 10.1109/NICS54270.2021.9701519
Son Huynh, Khiem H. Le, Nhi Dang, Bao Le, Dang T. Huynh, Binh T. Nguyen, T. T. Nguyen, N. Ho
With the booming development of the Internet and e-Commerce, advertising has appeared in almost all areas of life, especially in the real estate domain. Understanding these advertising posts is necessary to capture the status of real estate transactions and rent and sale prices in different areas with various properties. Motivated by that, we present the first manually annotated Vietnamese dataset in the real estate domain. Remarkably, our dataset is annotated for the named entity recognition task with lots of entity types. In comparison to other Vietnamese NER datasets, our dataset contains the largest number of entities. We empirically investigate a strong baseline on our dataset using the API supported by the spaCy library, which comprises four main components: tokenization, embedding, encoding, and parsing. For the encoding, we conduct experiments with various encoders, including Convolutions with Maxout activation (MaxoutWindowEncoder), Convolutions with Mish activation (MishWindowEncoder), and bidirectional Long short-term memory (BiLSTMEncoder). The experimental results show that the MishWindowEncoder gives the best performance in terms of micro F1-score (90.72 %). Finally, we aim to publish our dataset later to contribute to the current research community related to named entity recognition.
{"title":"Named Entity Recognition for Vietnamese Real Estate Advertisements","authors":"Son Huynh, Khiem H. Le, Nhi Dang, Bao Le, Dang T. Huynh, Binh T. Nguyen, T. T. Nguyen, N. Ho","doi":"10.1109/NICS54270.2021.9701519","DOIUrl":"https://doi.org/10.1109/NICS54270.2021.9701519","url":null,"abstract":"With the booming development of the Internet and e-Commerce, advertising has appeared in almost all areas of life, especially in the real estate domain. Understanding these advertising posts is necessary to capture the status of real estate transactions and rent and sale prices in different areas with various properties. Motivated by that, we present the first manually annotated Vietnamese dataset in the real estate domain. Remarkably, our dataset is annotated for the named entity recognition task with lots of entity types. In comparison to other Vietnamese NER datasets, our dataset contains the largest number of entities. We empirically investigate a strong baseline on our dataset using the API supported by the spaCy library, which comprises four main components: tokenization, embedding, encoding, and parsing. For the encoding, we conduct experiments with various encoders, including Convolutions with Maxout activation (MaxoutWindowEncoder), Convolutions with Mish activation (MishWindowEncoder), and bidirectional Long short-term memory (BiLSTMEncoder). The experimental results show that the MishWindowEncoder gives the best performance in terms of micro F1-score (90.72 %). Finally, we aim to publish our dataset later to contribute to the current research community related to named entity recognition.","PeriodicalId":296963,"journal":{"name":"2021 8th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126281185","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 : 2021-12-21DOI: 10.1109/NICS54270.2021.9701516
Phuoc-Hai Huynh, Trung-Nguyen Tran, Van Hoa Nguyen
The pandemic of COVID-19 is expansion and effect for human lives all over the world. Although many countries have been vaccinated, the number of new COVID-19 patients infected is still increasing. Recently, the detection of COVID-19 early can help find effective treatment plans using machine learning technologies algorithms. We propose the transfer learning models to detect pneumonia disease by this virus from chest X-Ray images. The public dataset is used in this work, and the new chest X-Ray images of COVID-19 patients are collected by An Giang Regional General Hospital. These images enrich the current public dataset and improve the performance prediction. Six transfer learning architectures are investigated using locally collected and public dataset. The experiment results show that the DenseNet121 transfer learning model outperforms others with the accuracy, precision, recall, F1-scores, and AUC of 98.51%, 98.54%, 98.51%, 98.05% and 99.15%, respectively on the augmented dataset and most algorithms process new data are improved performance.
{"title":"Enhancing COVID-19 prediction using transfer learning from Chest X-ray images","authors":"Phuoc-Hai Huynh, Trung-Nguyen Tran, Van Hoa Nguyen","doi":"10.1109/NICS54270.2021.9701516","DOIUrl":"https://doi.org/10.1109/NICS54270.2021.9701516","url":null,"abstract":"The pandemic of COVID-19 is expansion and effect for human lives all over the world. Although many countries have been vaccinated, the number of new COVID-19 patients infected is still increasing. Recently, the detection of COVID-19 early can help find effective treatment plans using machine learning technologies algorithms. We propose the transfer learning models to detect pneumonia disease by this virus from chest X-Ray images. The public dataset is used in this work, and the new chest X-Ray images of COVID-19 patients are collected by An Giang Regional General Hospital. These images enrich the current public dataset and improve the performance prediction. Six transfer learning architectures are investigated using locally collected and public dataset. The experiment results show that the DenseNet121 transfer learning model outperforms others with the accuracy, precision, recall, F1-scores, and AUC of 98.51%, 98.54%, 98.51%, 98.05% and 99.15%, respectively on the augmented dataset and most algorithms process new data are improved performance.","PeriodicalId":296963,"journal":{"name":"2021 8th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115260599","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 : 2021-12-21DOI: 10.1109/NICS54270.2021.9701543
Nguyen Minh Giang
This paper presents method and calculation program to determine working frequency for high frequency radio links reflected one time from the ionosphere. The calculation method takes into account the influence of ionospheric inhomogeneities on the characteristics of radio propagation. Experimental results have shown that the calculation program based on presented method has high accuracy and fast calculation speed.
{"title":"Prediction of Working Frequencies for Ionospheric Radio Links","authors":"Nguyen Minh Giang","doi":"10.1109/NICS54270.2021.9701543","DOIUrl":"https://doi.org/10.1109/NICS54270.2021.9701543","url":null,"abstract":"This paper presents method and calculation program to determine working frequency for high frequency radio links reflected one time from the ionosphere. The calculation method takes into account the influence of ionospheric inhomogeneities on the characteristics of radio propagation. Experimental results have shown that the calculation program based on presented method has high accuracy and fast calculation speed.","PeriodicalId":296963,"journal":{"name":"2021 8th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"158 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133138047","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 : 2021-12-10DOI: 10.1109/NICS54270.2021.9701553
T. Nguyen, T. Nguyen
Secrecy outage probability (SOP) and secrecy rate (SR) of the reconfigurable intelligent surface (RIS) assisted wireless networks under Rician fading are investigated in this paper. More precisely, we enhance the secrecy performance of the considered networks by suppressing the wiretap channel instead of maximizing the main channel. We propose a simple heuristic algorithm to find out the optimal phase-shift of each RIS’s element. Simulation results based on the Monte-Carlo method are given to verify the superiority of the proposed optimal phase-shifts compared to the random phase-shifts design.
{"title":"Secrecy Performance of RIS-assisted Wireless Networks under Rician fading","authors":"T. Nguyen, T. Nguyen","doi":"10.1109/NICS54270.2021.9701553","DOIUrl":"https://doi.org/10.1109/NICS54270.2021.9701553","url":null,"abstract":"Secrecy outage probability (SOP) and secrecy rate (SR) of the reconfigurable intelligent surface (RIS) assisted wireless networks under Rician fading are investigated in this paper. More precisely, we enhance the secrecy performance of the considered networks by suppressing the wiretap channel instead of maximizing the main channel. We propose a simple heuristic algorithm to find out the optimal phase-shift of each RIS’s element. Simulation results based on the Monte-Carlo method are given to verify the superiority of the proposed optimal phase-shifts compared to the random phase-shifts design.","PeriodicalId":296963,"journal":{"name":"2021 8th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121500892","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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