Pub Date : 2021-12-01DOI: 10.1109/uemcon53757.2021.9666655
Ihfaz Tahmid Morshed, Mohammad Monirujjaman Khan, Saife Shuhaib Md. Enan, Fahim Tanzil Takin
The objective of this study is to mitigate the impact of the ongoing Covid-19 pandemic. A web-based one-stop solution is proposed that aims to provide all the up-to-date information about the pandemic and work as a relay point of all the possible services that a patient may require. This can work as a newsfeed, market place, virtual care center, plasma bank and test center at the same time. Proposed services are handled by dedicated personnel via both wireless and online communication mediums. As a result, patients can access all possible services with a minimum effort, saving time. The system is developed using HTML5, CSS, PHP, MySQL and Bootstrap. All in all, this system can provide an all-in-one solution in order to slow down the progression of ongoing Covid-19 pandemic.
{"title":"Development of Web Based Online One Stop Platform to Fight Covid-19","authors":"Ihfaz Tahmid Morshed, Mohammad Monirujjaman Khan, Saife Shuhaib Md. Enan, Fahim Tanzil Takin","doi":"10.1109/uemcon53757.2021.9666655","DOIUrl":"https://doi.org/10.1109/uemcon53757.2021.9666655","url":null,"abstract":"The objective of this study is to mitigate the impact of the ongoing Covid-19 pandemic. A web-based one-stop solution is proposed that aims to provide all the up-to-date information about the pandemic and work as a relay point of all the possible services that a patient may require. This can work as a newsfeed, market place, virtual care center, plasma bank and test center at the same time. Proposed services are handled by dedicated personnel via both wireless and online communication mediums. As a result, patients can access all possible services with a minimum effort, saving time. The system is developed using HTML5, CSS, PHP, MySQL and Bootstrap. All in all, this system can provide an all-in-one solution in order to slow down the progression of ongoing Covid-19 pandemic.","PeriodicalId":127072,"journal":{"name":"2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125467964","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 : 2021-12-01DOI: 10.1109/UEMCON53757.2021.9666508
Kazi Nabiul Alam, Mohammad Monirujjaman Khan
Coronavirus disease COVID-19 is an infectious disease caused by a newly discovered coronavirus. COVID-19 virus affects the respiratory system of healthy individuals. Chest X-ray is one of the important imaging methods to identify the coronavirus. In deep learning, a convolutional neural network (CNN), is a class of deep learning models, most commonly applied for better outcomes to analyzing visual imagery. Automated covid-19 using Deep Learning techniques could, therefore, serve as an effective diagnostic aid. In this study, we used a convolutional neural network (CNN) for detecting COVID-19 from chest X-ray images. The overall project comprises various convolutional layers. The Max-pooling layers diminish the size of the picture significantly and by joining convolutional and pooling layers, the net is able to combine its features to learn more global features of the Image. Eventually, we utilize the highlights in two completely associated (Dense) layers. Dropout is a regularization strategy, where the layer arbitrarily replaces an extent of its weights to zero for each training sample. This forces the net to learn features in an appropriate way, not depending a lot on specific weight, and thus improves speculation and 'relu' is the activation function. Applying convolutional neural network which is a Deep Learning algorithm that can take in an input image, relegate significance to different perspectives in the images and have the option to separate one from the other.
{"title":"CNN Based COVID-19 Prediction from Chest X-ray Images","authors":"Kazi Nabiul Alam, Mohammad Monirujjaman Khan","doi":"10.1109/UEMCON53757.2021.9666508","DOIUrl":"https://doi.org/10.1109/UEMCON53757.2021.9666508","url":null,"abstract":"Coronavirus disease COVID-19 is an infectious disease caused by a newly discovered coronavirus. COVID-19 virus affects the respiratory system of healthy individuals. Chest X-ray is one of the important imaging methods to identify the coronavirus. In deep learning, a convolutional neural network (CNN), is a class of deep learning models, most commonly applied for better outcomes to analyzing visual imagery. Automated covid-19 using Deep Learning techniques could, therefore, serve as an effective diagnostic aid. In this study, we used a convolutional neural network (CNN) for detecting COVID-19 from chest X-ray images. The overall project comprises various convolutional layers. The Max-pooling layers diminish the size of the picture significantly and by joining convolutional and pooling layers, the net is able to combine its features to learn more global features of the Image. Eventually, we utilize the highlights in two completely associated (Dense) layers. Dropout is a regularization strategy, where the layer arbitrarily replaces an extent of its weights to zero for each training sample. This forces the net to learn features in an appropriate way, not depending a lot on specific weight, and thus improves speculation and 'relu' is the activation function. Applying convolutional neural network which is a Deep Learning algorithm that can take in an input image, relegate significance to different perspectives in the images and have the option to separate one from the other.","PeriodicalId":127072,"journal":{"name":"2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121493290","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}
This research presents the design of a system for the automated dosing of cattle feed through mechatronic systems. Control is established for each process to be performed as the drive of the belts, the weighing of the packages that are divided into 3 weights (1/2Kg, 1Kg, and 2Kg), also the distribution is these employing sensors and a force applied by a pivoting arm. Also, the addition of PLC optimized the process of recognizing the weight of the cows and the allocation of their ratio by taking as a variable the current weight at the time of weighing on the scale. In addition, the mechatronic system implemented will improve the quality of life of the cows, reduce feed investment losses and the time of feed distribution to the cows.
{"title":"Design of an Automated System for Cattle-Feed Dispensing in Cattle-Cows","authors":"Iraiz Lucero Quintanilla Mosquera, Jesus Eduardo Rosales Fierro, Jhon Rodrigo Ortiz Zacarias, Jhamir Beltran Montero, Sario Angel Chamorro Quijano, Deyby Huamanchahua","doi":"10.1109/UEMCON53757.2021.9666491","DOIUrl":"https://doi.org/10.1109/UEMCON53757.2021.9666491","url":null,"abstract":"This research presents the design of a system for the automated dosing of cattle feed through mechatronic systems. Control is established for each process to be performed as the drive of the belts, the weighing of the packages that are divided into 3 weights (1/2Kg, 1Kg, and 2Kg), also the distribution is these employing sensors and a force applied by a pivoting arm. Also, the addition of PLC optimized the process of recognizing the weight of the cows and the allocation of their ratio by taking as a variable the current weight at the time of weighing on the scale. In addition, the mechatronic system implemented will improve the quality of life of the cows, reduce feed investment losses and the time of feed distribution to the cows.","PeriodicalId":127072,"journal":{"name":"2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"421 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128973425","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}
Technology-wise, children are much ahead of their parents. Due to hectic schedules and daily struggles, time is limited for parents. For that reason, the AI-powered child protection system helps protect children from modern cyber-attacks while offering parents more control over their children. Keyloggers, keystroke and mouse movement loggers help to collect data and can record user behaviour and find patterns. Furthermore, the use of those records is able to detect children’s improper behaviour and reveal children’s emotional states. Behavioral Data Extractor and Risk Analysis systems can analyze huge numbers of URLs and web content recorded by proxy, as well as application usage and screen times collected by background service. The Smart Resource Restricter is designed to help parents and children navigate the web safely and appropriately. The research can identify and prevent child predators. Indeed, cyberbullying and phishing attacks cross many boundaries, causing great harm to the community. It blocks outside threats and notifies parents of sexual and other online predators that often target children. The PandaGuardian successfully achieved its goal with the assistance of different algorithms and the respective outcomes. The model evaluation report, which compares all the methods, is a guardian companion. Parents could get assistance in order to safeguard their children from the day-to-day evolving cyber threats.
{"title":"Intelligent Cyber Safe Framework for Children","authors":"Mohomed Harfath, Rahal Amrith, Navindu Dulanaka, Praveen Perera, Lakmal Rupersinga, C. Liyanapathirana","doi":"10.1109/UEMCON53757.2021.9666696","DOIUrl":"https://doi.org/10.1109/UEMCON53757.2021.9666696","url":null,"abstract":"Technology-wise, children are much ahead of their parents. Due to hectic schedules and daily struggles, time is limited for parents. For that reason, the AI-powered child protection system helps protect children from modern cyber-attacks while offering parents more control over their children. Keyloggers, keystroke and mouse movement loggers help to collect data and can record user behaviour and find patterns. Furthermore, the use of those records is able to detect children’s improper behaviour and reveal children’s emotional states. Behavioral Data Extractor and Risk Analysis systems can analyze huge numbers of URLs and web content recorded by proxy, as well as application usage and screen times collected by background service. The Smart Resource Restricter is designed to help parents and children navigate the web safely and appropriately. The research can identify and prevent child predators. Indeed, cyberbullying and phishing attacks cross many boundaries, causing great harm to the community. It blocks outside threats and notifies parents of sexual and other online predators that often target children. The PandaGuardian successfully achieved its goal with the assistance of different algorithms and the respective outcomes. The model evaluation report, which compares all the methods, is a guardian companion. Parents could get assistance in order to safeguard their children from the day-to-day evolving cyber threats.","PeriodicalId":127072,"journal":{"name":"2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130439034","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 : 2021-12-01DOI: 10.1109/UEMCON53757.2021.9666733
D. Dissanayake, R. Rajapaksha, U. P. Prabhashawara, S. A. D. S. P. Solanga, J. Jayakody
Due to a lack of knowledge about the building structure and possible impediments, the majority of blind persons require assistance when traveling through unknown regions. To solve this issue, this paper provides "Guide-Me" as a strategy for indoor navigation with optimum accessibility, usability, and security, decreasing obstacles that the user may meet when traveling through indoor surroundings. Because the intended audience for this research is blind or visually impaired persons, "Guide-Me" makes use of the user’s voice-based inputs. This paper also includes Bluetooth beacon integration for localization, a Smart stick with sensors for obstacle detection, a machine learning model for voice authentication, and an algorithm protocol for a secure connection between server and application Integration driven architecture to assist vision impaired in navigating the known and unknown indoor environment.
{"title":"Guide-Me: Voice authenticated indoor user guidance system","authors":"D. Dissanayake, R. Rajapaksha, U. P. Prabhashawara, S. A. D. S. P. Solanga, J. Jayakody","doi":"10.1109/UEMCON53757.2021.9666733","DOIUrl":"https://doi.org/10.1109/UEMCON53757.2021.9666733","url":null,"abstract":"Due to a lack of knowledge about the building structure and possible impediments, the majority of blind persons require assistance when traveling through unknown regions. To solve this issue, this paper provides \"Guide-Me\" as a strategy for indoor navigation with optimum accessibility, usability, and security, decreasing obstacles that the user may meet when traveling through indoor surroundings. Because the intended audience for this research is blind or visually impaired persons, \"Guide-Me\" makes use of the user’s voice-based inputs. This paper also includes Bluetooth beacon integration for localization, a Smart stick with sensors for obstacle detection, a machine learning model for voice authentication, and an algorithm protocol for a secure connection between server and application Integration driven architecture to assist vision impaired in navigating the known and unknown indoor environment.","PeriodicalId":127072,"journal":{"name":"2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132445055","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 : 2021-12-01DOI: 10.1109/UEMCON53757.2021.9666603
Jamal Alotaibi, Lubna K. Alazzawi
The advancement of the Internet-of-Vehicles (IoV) innovation aids the development of intelligent transportation systems (ITS). There are several interoperability challenges in today’s IoV networks, such as security and privacy issues, information irregularity, and so on. Because vehicle data is private and sensitive, it necessitates extra caution. Authentication of communicating devices is one such technique for securing data. The information sent via public channels is secured using authentication. Many protocols have been developed; however, traditional authentication models cannot be applied directly to circumstances needing low latency in particular. Furthermore, they are ineffective for two primary reasons: first, they are unable to adapt to the growing volume of data collected, and second, they are prone to cyber-attacks. As a result, in this paper, we attempt to propose a viable solution that is fully robust and overcomes the aforementioned problems. To protect IoV devices data during communication, we designed a lightweight and fog-based authentication scheme. Our approach ensures minimal communication cost and complies with high-security standards. Finally, we assess and compare our method’s performance in terms of network parameters such as throughput, end-to-end delay, and the rate of packet loss. Results indicate that our method scale well with the increasing number of vehicles while maintaining a minimal communication cost.
{"title":"A Lightweight and Fog-based Authentication Scheme for Internet-of-Vehicles","authors":"Jamal Alotaibi, Lubna K. Alazzawi","doi":"10.1109/UEMCON53757.2021.9666603","DOIUrl":"https://doi.org/10.1109/UEMCON53757.2021.9666603","url":null,"abstract":"The advancement of the Internet-of-Vehicles (IoV) innovation aids the development of intelligent transportation systems (ITS). There are several interoperability challenges in today’s IoV networks, such as security and privacy issues, information irregularity, and so on. Because vehicle data is private and sensitive, it necessitates extra caution. Authentication of communicating devices is one such technique for securing data. The information sent via public channels is secured using authentication. Many protocols have been developed; however, traditional authentication models cannot be applied directly to circumstances needing low latency in particular. Furthermore, they are ineffective for two primary reasons: first, they are unable to adapt to the growing volume of data collected, and second, they are prone to cyber-attacks. As a result, in this paper, we attempt to propose a viable solution that is fully robust and overcomes the aforementioned problems. To protect IoV devices data during communication, we designed a lightweight and fog-based authentication scheme. Our approach ensures minimal communication cost and complies with high-security standards. Finally, we assess and compare our method’s performance in terms of network parameters such as throughput, end-to-end delay, and the rate of packet loss. Results indicate that our method scale well with the increasing number of vehicles while maintaining a minimal communication cost.","PeriodicalId":127072,"journal":{"name":"2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134099550","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 : 2021-12-01DOI: 10.1109/uemcon53757.2021.9666654
Md. Yearat Hossain, Ifran Rahman Nijhum, Abu Adnan Sadi, Md. Tazin Morshed Shad, Rashedur M. Rahman
In recent years, visual pollution has become a major concern in rapidly rising cities. This research deals with detecting visual pollutants from the street images collected using Google Street View. For this experiment, we chose the streets of Dhaka, the capital city of Bangladesh, to build our image dataset, mainly because Dhaka was ranked recently as one the most polluted cities in the world. However, the methods shown in this study can be applied to images of any city around the world and would produce close to a similar output. Throughout this study, we tried to portray the possible utilisation of Google Street View in building datasets and how this data can be used to solve environmental pollution with the help of deep learning. The image dataset was created manually by taking screenshots from various angles of every street view with visual pollutants in the frame. The images were then manually annotated using CVAT and were fed into the model for training. For the detection, we have used the object detection model YOLOv5 to detect all the visual pollutants present in the image. Finally, we evaluated the results achieved from this study and gave direction of using the outcome from this study in different domains.
{"title":"Visual Pollution Detection Using Google Street View and YOLO","authors":"Md. Yearat Hossain, Ifran Rahman Nijhum, Abu Adnan Sadi, Md. Tazin Morshed Shad, Rashedur M. Rahman","doi":"10.1109/uemcon53757.2021.9666654","DOIUrl":"https://doi.org/10.1109/uemcon53757.2021.9666654","url":null,"abstract":"In recent years, visual pollution has become a major concern in rapidly rising cities. This research deals with detecting visual pollutants from the street images collected using Google Street View. For this experiment, we chose the streets of Dhaka, the capital city of Bangladesh, to build our image dataset, mainly because Dhaka was ranked recently as one the most polluted cities in the world. However, the methods shown in this study can be applied to images of any city around the world and would produce close to a similar output. Throughout this study, we tried to portray the possible utilisation of Google Street View in building datasets and how this data can be used to solve environmental pollution with the help of deep learning. The image dataset was created manually by taking screenshots from various angles of every street view with visual pollutants in the frame. The images were then manually annotated using CVAT and were fed into the model for training. For the detection, we have used the object detection model YOLOv5 to detect all the visual pollutants present in the image. Finally, we evaluated the results achieved from this study and gave direction of using the outcome from this study in different domains.","PeriodicalId":127072,"journal":{"name":"2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124176832","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 : 2021-12-01DOI: 10.1109/uemcon53757.2021.9666489
Mahfuzur Rahman, B. Morshed
Respiratory behavior is one of the important parameters that indicate any physiological changes in human body. However, using a respiration sensor device for continuous monitoring is inconvenient and expensive. In this paper, an approach to acquire the respiration signal from the wrist electrocardiogram (ECG) is proposed. An analog front end (AFE) sampled at 100 Hz is used to collect ECG signals from the wrist to compute and verify the corresponding heart rate (HR) with a commercial ECG device. Signal processing mechanisms are applied on the raw data to denoise the ECG signal. The captured ECG signal is further processed to extract a breathing pattern to calculate a respiration rate (RR) in breath per minute (BPM). The extracted BPMs are compared with a commercial respiration monitor to validate the data by following a protocol at 5 different BPMs (12, 15, 20, 24 and 30). For each BPM, commercial respiration monitor is validated at first. Then, data are taken simultaneously wearing wrist electrodes and commercial respiratory device to validate the performance of our proposed method at different BPMs. The results indicate high accuracy of the proposed system which is low-cost, simpler to implement, can be integrated with a wearable device and remove the demand of any dedicated sensor for RR measurements.
{"title":"Extraction of Respiration Rate from Wrist ECG Signals","authors":"Mahfuzur Rahman, B. Morshed","doi":"10.1109/uemcon53757.2021.9666489","DOIUrl":"https://doi.org/10.1109/uemcon53757.2021.9666489","url":null,"abstract":"Respiratory behavior is one of the important parameters that indicate any physiological changes in human body. However, using a respiration sensor device for continuous monitoring is inconvenient and expensive. In this paper, an approach to acquire the respiration signal from the wrist electrocardiogram (ECG) is proposed. An analog front end (AFE) sampled at 100 Hz is used to collect ECG signals from the wrist to compute and verify the corresponding heart rate (HR) with a commercial ECG device. Signal processing mechanisms are applied on the raw data to denoise the ECG signal. The captured ECG signal is further processed to extract a breathing pattern to calculate a respiration rate (RR) in breath per minute (BPM). The extracted BPMs are compared with a commercial respiration monitor to validate the data by following a protocol at 5 different BPMs (12, 15, 20, 24 and 30). For each BPM, commercial respiration monitor is validated at first. Then, data are taken simultaneously wearing wrist electrodes and commercial respiratory device to validate the performance of our proposed method at different BPMs. The results indicate high accuracy of the proposed system which is low-cost, simpler to implement, can be integrated with a wearable device and remove the demand of any dedicated sensor for RR measurements.","PeriodicalId":127072,"journal":{"name":"2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116670977","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 : 2021-12-01DOI: 10.1109/UEMCON53757.2021.9666686
Hassan Musafer, M. Faezipour
An efficient and distortionless partitioning scheme for the Partial Transmit Sequence (PTS) method is proposed to control the nonlinear property producing other peaks in the Orthogonal Frequency Division Multiplexing (OFDM) transmit signal. The approach is flexible and works with a limited and controlled number of subcarriers and can significantly improve peak power statistics of the optimized transmit signal. The traditional partitioning strategy of the PTS method allows all subchannels/subcarriers to contribute in the reduction of the peak-to-average power ratio (PAPR). Therefore, the traditional scheme is ineffective for controlling the nonlinear property, which may produce other peaks by rotating all subchannels of the OFDM signal. Although the PTS method can optimize the value of PAPR, the effect of the nonlinear property of the PTS method has not been properly addressed in the literature. In this paper, we examine the number of actual parameters/rotations used in the PTS method by suitably testing the nonlinear property on the rotated partial sequences. In contrast to the traditional partitioning strategy, the proposed strategy involves rotating half of the separated subcarriers to eliminate the effect of producing other peaks. The traditional and proposed schemes are compared through simulation results with respect to the required system complexity and the minimum PAPR of the OFDM transmit signal. Finally, it is shown that the controlled partitioning scheme is closer to the theoretical limit of PAPR optimization, and it also requires less system complexity than the traditional scheme.
{"title":"A Novel Partitioning Scheme for Partial Transmit Sequence Method","authors":"Hassan Musafer, M. Faezipour","doi":"10.1109/UEMCON53757.2021.9666686","DOIUrl":"https://doi.org/10.1109/UEMCON53757.2021.9666686","url":null,"abstract":"An efficient and distortionless partitioning scheme for the Partial Transmit Sequence (PTS) method is proposed to control the nonlinear property producing other peaks in the Orthogonal Frequency Division Multiplexing (OFDM) transmit signal. The approach is flexible and works with a limited and controlled number of subcarriers and can significantly improve peak power statistics of the optimized transmit signal. The traditional partitioning strategy of the PTS method allows all subchannels/subcarriers to contribute in the reduction of the peak-to-average power ratio (PAPR). Therefore, the traditional scheme is ineffective for controlling the nonlinear property, which may produce other peaks by rotating all subchannels of the OFDM signal. Although the PTS method can optimize the value of PAPR, the effect of the nonlinear property of the PTS method has not been properly addressed in the literature. In this paper, we examine the number of actual parameters/rotations used in the PTS method by suitably testing the nonlinear property on the rotated partial sequences. In contrast to the traditional partitioning strategy, the proposed strategy involves rotating half of the separated subcarriers to eliminate the effect of producing other peaks. The traditional and proposed schemes are compared through simulation results with respect to the required system complexity and the minimum PAPR of the OFDM transmit signal. Finally, it is shown that the controlled partitioning scheme is closer to the theoretical limit of PAPR optimization, and it also requires less system complexity than the traditional scheme.","PeriodicalId":127072,"journal":{"name":"2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122049913","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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