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/uemcon53757.2021.9666570
Gan Luan, N. Beaulieu, Xianpeng Wang, Mengxing Huang
A buffer-aided collision resolution scheme for UHF RFID is proposed. The scheme uses buffers to store the collided signal, so collision resolution can be achieved through subtracting the identified signals from the corrupted signal stored in the buffer. Based on the buffer-aided collision resolution technique, a novel buffer-aided dynamic frame-slotted Aloha algorithm with the ability to resolve m-tag-collided slots (B-DFSA-m) is introduced. Simulations show that the system efficiencies of B-DFSA-m with the ability to resolve m = 2, 3, and 4-tag-collided slots are 55%, 64%, 66.5%, and their time efficiencies are 72%, 74%, and 75%. These system and time efficiencies compare favorably with the efficiencies of Q-algorithm, Schoute, MAPP, FEIA, and ILCM, BE-MDT, ds-DFSA, ABTSA, and DBTSA, which are the best previous collision resolution schemes for UHF RFID.
{"title":"Buffer-Aided Collision Resolution for UHF RFID","authors":"Gan Luan, N. Beaulieu, Xianpeng Wang, Mengxing Huang","doi":"10.1109/uemcon53757.2021.9666570","DOIUrl":"https://doi.org/10.1109/uemcon53757.2021.9666570","url":null,"abstract":"A buffer-aided collision resolution scheme for UHF RFID is proposed. The scheme uses buffers to store the collided signal, so collision resolution can be achieved through subtracting the identified signals from the corrupted signal stored in the buffer. Based on the buffer-aided collision resolution technique, a novel buffer-aided dynamic frame-slotted Aloha algorithm with the ability to resolve m-tag-collided slots (B-DFSA-m) is introduced. Simulations show that the system efficiencies of B-DFSA-m with the ability to resolve m = 2, 3, and 4-tag-collided slots are 55%, 64%, 66.5%, and their time efficiencies are 72%, 74%, and 75%. These system and time efficiencies compare favorably with the efficiencies of Q-algorithm, Schoute, MAPP, FEIA, and ILCM, BE-MDT, ds-DFSA, ABTSA, and DBTSA, which are the best previous collision resolution schemes for UHF RFID.","PeriodicalId":127072,"journal":{"name":"2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"1 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":"129550269","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/uemcon53757.2021.9666576
Mau-Luen Tham, Y. Wong, Ban-Hoe Kwan, Y. Owada, M. Sein, Yoong Choon Chang
Recent advances in deep learning and computer vision have transformed surveillance into an important application for smart disaster monitoring systems. Based on the detected number of victims and activity of disasters, emergency response unit can dispatch manpower more efficiently, which could save more lives. However, most of existing disaster detection methods fall into the class of single-task learning, which can either detect victim or classify disaster. In contrast, this paper proposes a YOLO-based multi-task model which performs the aforementioned tasks simultaneously. This is accomplished by attaching a disaster classification head model to the backbone of a victim detection model. The head model is inherited from the MobileNetv2 architecture, and we precisely select the backbone feature map layer to which the head model is attached. For the victim detection, results reveal that the solution achieves up to 0.6938 and 20.31 in terms of average precision and frame per second, respectively. Whereas for the disaster classification, the algorithm is comparable with most deep learning models that are specifically trained for single task. This shows that our solution is flexible and robust enough to handle both victim detection and disaster classification.
{"title":"Joint Disaster Classification and Victim Detection using Multi-Task Learning","authors":"Mau-Luen Tham, Y. Wong, Ban-Hoe Kwan, Y. Owada, M. Sein, Yoong Choon Chang","doi":"10.1109/uemcon53757.2021.9666576","DOIUrl":"https://doi.org/10.1109/uemcon53757.2021.9666576","url":null,"abstract":"Recent advances in deep learning and computer vision have transformed surveillance into an important application for smart disaster monitoring systems. Based on the detected number of victims and activity of disasters, emergency response unit can dispatch manpower more efficiently, which could save more lives. However, most of existing disaster detection methods fall into the class of single-task learning, which can either detect victim or classify disaster. In contrast, this paper proposes a YOLO-based multi-task model which performs the aforementioned tasks simultaneously. This is accomplished by attaching a disaster classification head model to the backbone of a victim detection model. The head model is inherited from the MobileNetv2 architecture, and we precisely select the backbone feature map layer to which the head model is attached. For the victim detection, results reveal that the solution achieves up to 0.6938 and 20.31 in terms of average precision and frame per second, respectively. Whereas for the disaster classification, the algorithm is comparable with most deep learning models that are specifically trained for single task. This shows that our solution is flexible and robust enough to handle both victim detection and disaster classification.","PeriodicalId":127072,"journal":{"name":"2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"26 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":"128259220","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/uemcon53757.2021.9666655
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}
In this paper, a wireless nurse calling system is proposed where any patient can call a nurse for an emergency case, and the notification will be received in the nurse’s wrist band. Currently, most of the emergency calling systems in a hospital are constructed based on hard-wired, which is a costly approach. There have been an attempt to implement the calling system over a wireless network, but the scale of coverage was very tiny. This project is based on a unified WiFi network which highly accessible and cheap to found, thus making it one of the cheapest approaches in this domain. The key component of this project is a WiFi module ESP8266 and a Server. This project can also be used on any kind of scale depending on the needs, ie. auto attendence and location detection. Our proposed system promises to deliver much higher performance and coverage while it is closing the gap between the management and nurses by monitoring calls in real-time.
{"title":"An IOT Based Nurse Calling System for Real-time Emergency Alert Using Local Wireless Network","authors":"Omar Faruk Riyad, Ahraf Sharif, Arif-ur-Rahman Chowdhury Suhan, Mohammad Monirujjaman Khan","doi":"10.1109/uemcon53757.2021.9666705","DOIUrl":"https://doi.org/10.1109/uemcon53757.2021.9666705","url":null,"abstract":"In this paper, a wireless nurse calling system is proposed where any patient can call a nurse for an emergency case, and the notification will be received in the nurse’s wrist band. Currently, most of the emergency calling systems in a hospital are constructed based on hard-wired, which is a costly approach. There have been an attempt to implement the calling system over a wireless network, but the scale of coverage was very tiny. This project is based on a unified WiFi network which highly accessible and cheap to found, thus making it one of the cheapest approaches in this domain. The key component of this project is a WiFi module ESP8266 and a Server. This project can also be used on any kind of scale depending on the needs, ie. auto attendence and location detection. Our proposed system promises to deliver much higher performance and coverage while it is closing the gap between the management and nurses by monitoring calls in real-time.","PeriodicalId":127072,"journal":{"name":"2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"40 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":"129695424","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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