Pub Date : 2022-12-09DOI: 10.1109/ICCC56324.2022.10065902
Yudong Jia, Ningbo Zhang
In today's era, there is a growing concern about data privacy and security. Data is the foundation of machine learning, and due to the complexity of the reality, data often exists in silos. The great development of computing and storage capacity of edge devices has made it possible to train machine learning models on edge devices with data. Federated learning is a special kind of distributed machine learning in which multiple distributed clients use local data to train a model and upload the resulting model parameters to a central server for aggregation and iteration to finally obtain a global model with good generalization performance. The interaction between the clients and the server is model parameters rather than the data itself, which effectively protects data privacy and security. After research, it is found that Federated Learning is mainly divided into two aggregation models: synchronous aggregation and asynchronous aggregation. In this paper, the classical FedAvg synchronous federated average aggregation algorithm is analyzed. The central server needs to wait for all participating nodes to be trained before aggregating and updating the model, which is inconvenient to achieve global synchronization on resource heterogeneous clients. To improve the utilization of computational resources, FedAsync, an asynchronous federated learning aggregation mechanism with a receivable window based on dual weights, which are data volume size weight and staleness weight, is proposed. And FedAvg and FedAsync are tested and analyzed. Based on this, the impact on federated learning due to asynchronous data arrival rate and limited communication resources is further explored.
{"title":"Research and Implementation of Asynchronous Transmission and Update Strategy for Federated Learning","authors":"Yudong Jia, Ningbo Zhang","doi":"10.1109/ICCC56324.2022.10065902","DOIUrl":"https://doi.org/10.1109/ICCC56324.2022.10065902","url":null,"abstract":"In today's era, there is a growing concern about data privacy and security. Data is the foundation of machine learning, and due to the complexity of the reality, data often exists in silos. The great development of computing and storage capacity of edge devices has made it possible to train machine learning models on edge devices with data. Federated learning is a special kind of distributed machine learning in which multiple distributed clients use local data to train a model and upload the resulting model parameters to a central server for aggregation and iteration to finally obtain a global model with good generalization performance. The interaction between the clients and the server is model parameters rather than the data itself, which effectively protects data privacy and security. After research, it is found that Federated Learning is mainly divided into two aggregation models: synchronous aggregation and asynchronous aggregation. In this paper, the classical FedAvg synchronous federated average aggregation algorithm is analyzed. The central server needs to wait for all participating nodes to be trained before aggregating and updating the model, which is inconvenient to achieve global synchronization on resource heterogeneous clients. To improve the utilization of computational resources, FedAsync, an asynchronous federated learning aggregation mechanism with a receivable window based on dual weights, which are data volume size weight and staleness weight, is proposed. And FedAvg and FedAsync are tested and analyzed. Based on this, the impact on federated learning due to asynchronous data arrival rate and limited communication resources is further explored.","PeriodicalId":263098,"journal":{"name":"2022 IEEE 8th International Conference on Computer and Communications (ICCC)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129072251","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}
DevOps (development and operations) methodology, as the integration of agile software development method and lean concept, has aroused great interest and concern in the software industry in recent years. The application value of DevOps has been widely recognized by the whole industry due to its massive advantages, such as the significantly decreased time to production, in-creased reliability and stability. However, currently very limited application cases have been reported while there is almost no large-scale application of DevOps software platform. In this study, we have proposed and built an end-to-end and innovative DevOps platform of the whole process, namely the YunDao platform. The system design of the YunDao platform, mainly including the overall architecture, technical architecture, development architecture and functional architecture, was systematically presented and discussed. This work can be considered as a breakthrough in the field of commercial application of large-scale DevOps platform.
DevOps (development and operations)方法学作为敏捷软件开发方法与精益理念的融合，近年来引起了软件界的极大兴趣和关注。DevOps的应用价值已经得到了整个行业的广泛认可，因为它具有巨大的优势，比如显著缩短了生产时间，提高了可靠性和稳定性。然而，目前报道的应用案例非常有限，DevOps软件平台的大规模应用几乎没有。在本研究中，我们提出并搭建了一个端到端的创新型全流程DevOps平台，即云道平台。系统地介绍和讨论了运道平台的系统设计，主要包括总体架构、技术架构、开发架构和功能架构。这项工作可以被认为是大规模DevOps平台商业应用领域的一个突破。
{"title":"Towards Development of a Novel DevOps Platform for Ultra-Large-Scale Commercial Applications: Part 1- System Design","authors":"Mengxia Chen, Jiangang Tong, Lanying Shi, Man Li, Wensheng Yao, Huan Liang","doi":"10.1109/ICCC56324.2022.10065670","DOIUrl":"https://doi.org/10.1109/ICCC56324.2022.10065670","url":null,"abstract":"DevOps (development and operations) methodology, as the integration of agile software development method and lean concept, has aroused great interest and concern in the software industry in recent years. The application value of DevOps has been widely recognized by the whole industry due to its massive advantages, such as the significantly decreased time to production, in-creased reliability and stability. However, currently very limited application cases have been reported while there is almost no large-scale application of DevOps software platform. In this study, we have proposed and built an end-to-end and innovative DevOps platform of the whole process, namely the YunDao platform. The system design of the YunDao platform, mainly including the overall architecture, technical architecture, development architecture and functional architecture, was systematically presented and discussed. This work can be considered as a breakthrough in the field of commercial application of large-scale DevOps platform.","PeriodicalId":263098,"journal":{"name":"2022 IEEE 8th International Conference on Computer and Communications (ICCC)","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131492689","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}
The accurate measurement of blood flow velocities is of great importance for the prevention, early diagnosis, and course monitoring of atherosclerosis. Unlike the conventional speckle tracking using the pre-defined kernels (STPK), an improved speckle tracking using the dynamical kernels (STDK) based on ultrafast ultrasound is proposed to improve the accuracy and efficiency of the blood flow velocity profile (BFVP) estimation in this work. The novelty of this study is that the coordinate of the current tracked kernel in the reference frame is dynamically adjusted according to the coordinate of the best matching of the last tracked kernel in the comparison frame. This modification is not only fault-tolerant to a certain degree for speckle decorrelation, but also reduces the time consumption produced by traversing the whole search regions. The performance of the proposed STDK was validated via simulations. Compared with the STPK-based results, the NRMSE and acquisition time of the STDK-based results decrease by 48.39% and 36.8% on average, respectively. Therefore, the proposed STDK method has been proven to improve the accuracy, efficiency of the BFVP estimation, which is helpful for clinical diagnosis and treatment of related diseases.
{"title":"Ultrafast Ultrasound Speckle Tracking Using the Dynamical Kernels for Improved Blood Flow Velocity Profiling","authors":"Yue Zhang, Bingbing He, Yufeng Zhang, Zhiyao Li, Xun Lang, Junhua Zhang","doi":"10.1109/ICCC56324.2022.10065614","DOIUrl":"https://doi.org/10.1109/ICCC56324.2022.10065614","url":null,"abstract":"The accurate measurement of blood flow velocities is of great importance for the prevention, early diagnosis, and course monitoring of atherosclerosis. Unlike the conventional speckle tracking using the pre-defined kernels (STPK), an improved speckle tracking using the dynamical kernels (STDK) based on ultrafast ultrasound is proposed to improve the accuracy and efficiency of the blood flow velocity profile (BFVP) estimation in this work. The novelty of this study is that the coordinate of the current tracked kernel in the reference frame is dynamically adjusted according to the coordinate of the best matching of the last tracked kernel in the comparison frame. This modification is not only fault-tolerant to a certain degree for speckle decorrelation, but also reduces the time consumption produced by traversing the whole search regions. The performance of the proposed STDK was validated via simulations. Compared with the STPK-based results, the NRMSE and acquisition time of the STDK-based results decrease by 48.39% and 36.8% on average, respectively. Therefore, the proposed STDK method has been proven to improve the accuracy, efficiency of the BFVP estimation, which is helpful for clinical diagnosis and treatment of related diseases.","PeriodicalId":263098,"journal":{"name":"2022 IEEE 8th International Conference on Computer and Communications (ICCC)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133964444","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-09DOI: 10.1109/ICCC56324.2022.10065737
Wanjun Li, Zhe Liu, Hongtao Deng
High-resolution (HR) astronomical image play a vital role in the development of scientific research, cosmic exploration, astronomy, and physics. In this paper, we propose a self- attention based generative adversarial network of astronomical image super-resolution (SR) aiming at the problem of low- resolution (LR) of astronomical imaging systems. We adopt SRGAN as the benchmark model and add self-attention, which captures more global dependencies and deepens the network for enhanced high-frequency feature representation. To achieve fast and stable training, the BN layer is deleted from the proposed networks. The Charbonnier loss is introduced as the loss function to handle outliers and improve SR performance. Experimental results demonstrate that the proposed method is able to reduce artifacts and obtains better performance in Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) on the astronomical image testset.
{"title":"A Self-Attention Based SRGAN for Super-Resolution of Astronomical Image","authors":"Wanjun Li, Zhe Liu, Hongtao Deng","doi":"10.1109/ICCC56324.2022.10065737","DOIUrl":"https://doi.org/10.1109/ICCC56324.2022.10065737","url":null,"abstract":"High-resolution (HR) astronomical image play a vital role in the development of scientific research, cosmic exploration, astronomy, and physics. In this paper, we propose a self- attention based generative adversarial network of astronomical image super-resolution (SR) aiming at the problem of low- resolution (LR) of astronomical imaging systems. We adopt SRGAN as the benchmark model and add self-attention, which captures more global dependencies and deepens the network for enhanced high-frequency feature representation. To achieve fast and stable training, the BN layer is deleted from the proposed networks. The Charbonnier loss is introduced as the loss function to handle outliers and improve SR performance. Experimental results demonstrate that the proposed method is able to reduce artifacts and obtains better performance in Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) on the astronomical image testset.","PeriodicalId":263098,"journal":{"name":"2022 IEEE 8th International Conference on Computer and Communications (ICCC)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133717205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-09DOI: 10.1109/ICCC56324.2022.10065926
Jiawen Yin, Guomei Zhang, Yue Li, Guobing Li
To avoid the high calculating requirement of the central node in the centralized positioning system, a distributed scheme with multiple localization sub-networks to localize an unknown radiation source (RS) is discussed in this paper. Furthermore, in order to reduce the adverse effect of the potential information loss in the parameter estimation of the traditional two-step localization algorithm, a neural network to deduce the objective position from the hybrid localization parameters is designed for each sub-network to replace the solving of positioning equations involved in the two-step localizer. Finally, in order to obtain more accurate localization results, two fusion methods based on the weighted sum and the neural network are given at the final control center to fuse the localization results of all the sub-networks. The experimental results show that the proposed scheme significantly outperforms the traditional single-parameter based two-step localization method even though the latter one adopts the centralized positioning strategy. Furthermore, the neural network based fusion method can improve the final positioning precision obviously for signal to noise ratio (SNR) higher than 10dB.
{"title":"A Distributed Positioning Scheme Based on Neural Network for Radiation Source","authors":"Jiawen Yin, Guomei Zhang, Yue Li, Guobing Li","doi":"10.1109/ICCC56324.2022.10065926","DOIUrl":"https://doi.org/10.1109/ICCC56324.2022.10065926","url":null,"abstract":"To avoid the high calculating requirement of the central node in the centralized positioning system, a distributed scheme with multiple localization sub-networks to localize an unknown radiation source (RS) is discussed in this paper. Furthermore, in order to reduce the adverse effect of the potential information loss in the parameter estimation of the traditional two-step localization algorithm, a neural network to deduce the objective position from the hybrid localization parameters is designed for each sub-network to replace the solving of positioning equations involved in the two-step localizer. Finally, in order to obtain more accurate localization results, two fusion methods based on the weighted sum and the neural network are given at the final control center to fuse the localization results of all the sub-networks. The experimental results show that the proposed scheme significantly outperforms the traditional single-parameter based two-step localization method even though the latter one adopts the centralized positioning strategy. Furthermore, the neural network based fusion method can improve the final positioning precision obviously for signal to noise ratio (SNR) higher than 10dB.","PeriodicalId":263098,"journal":{"name":"2022 IEEE 8th International Conference on Computer and Communications (ICCC)","volume":"131 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122452707","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}
The pre-coding algorithm is used to reduce channel interference in visible light communication (VLC) system in this paper. After comparing the traditional ZF, MMSE and THP precoding algorithms, it is found that the optimal anti-interference scheme of the system is THP algorithm in 4 x 4 sender and receiver systems. Based on this, the paper proposes an optimized THP algorithm, which alters the row sequence of channel matrix $H$ and controls the emitter power. Simulation results show that the bit error rate (BER) of the system under the power-based THP algorithm is between 10–5 and 10–4, which greatly improves the performance of the system.
{"title":"Sorting and Power Allocation-Based THP Precoding Algorithm in VLC System","authors":"Furong Zhu, Liwei Yang, Wencong Lai, Junning Zhang, Xue Liang, Yanling Cai","doi":"10.1109/ICCC56324.2022.10065730","DOIUrl":"https://doi.org/10.1109/ICCC56324.2022.10065730","url":null,"abstract":"The pre-coding algorithm is used to reduce channel interference in visible light communication (VLC) system in this paper. After comparing the traditional ZF, MMSE and THP precoding algorithms, it is found that the optimal anti-interference scheme of the system is THP algorithm in 4 x 4 sender and receiver systems. Based on this, the paper proposes an optimized THP algorithm, which alters the row sequence of channel matrix $H$ and controls the emitter power. Simulation results show that the bit error rate (BER) of the system under the power-based THP algorithm is between 10–5 and 10–4, which greatly improves the performance of the system.","PeriodicalId":263098,"journal":{"name":"2022 IEEE 8th International Conference on Computer and Communications (ICCC)","volume":"313 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122751007","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}
Security and stability control system (SSCS) is the second defense line of power system. In ultra-large scale power grid, the existing SSCS adopts multi-level vertical configuration, which has problems such as poor coordination, weak dynamic redundancy and backup, and high failure risk. In order to ensure the secure and stable operation of super large scale power grid, this paper optimizes its topological structure and operation mechanism according to the development trend of power grid and the failure risk of stability control system. A flat SSCS is proposed and its system architecture and communication networking technology are introduced in details, as well as a specific design example. Finally, the paper summarizes the technical challenges of flat SSCS and puts forward some solutions.
{"title":"Networking Architecture and Key Technologies of Flat Security and Stability Control System","authors":"Kaiqiang Gao, Huixia Ding, Yanan Wang, Geng Zhang, Wei Han, Xuerang Guo, Wenyan Duan","doi":"10.1109/ICCC56324.2022.10065962","DOIUrl":"https://doi.org/10.1109/ICCC56324.2022.10065962","url":null,"abstract":"Security and stability control system (SSCS) is the second defense line of power system. In ultra-large scale power grid, the existing SSCS adopts multi-level vertical configuration, which has problems such as poor coordination, weak dynamic redundancy and backup, and high failure risk. In order to ensure the secure and stable operation of super large scale power grid, this paper optimizes its topological structure and operation mechanism according to the development trend of power grid and the failure risk of stability control system. A flat SSCS is proposed and its system architecture and communication networking technology are introduced in details, as well as a specific design example. Finally, the paper summarizes the technical challenges of flat SSCS and puts forward some solutions.","PeriodicalId":263098,"journal":{"name":"2022 IEEE 8th International Conference on Computer and Communications (ICCC)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117281968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-09DOI: 10.1109/ICCC56324.2022.10065783
Feng Wang, Chaojie Yang, H. Du, Shancheng Zhao
The spatially coupled turbo-like codes (SC-TCs) provide a new way to trade-off the performances between the water-fall region and the error-floor region. As a subclass of SC-TCs, spatially coupled serially concatenated codes (SC-SCCs) admit good performances in the error-floor region. This paper is concerned with the construction of SC-SCCs with improved water-fall performances. Particularly, we present the multidimensionally coupled serially concatenated codes (MC-SCCs), in which multiple SC-SCCs are coupled together in a cyclic manner. Two different decoding schedules are presented for the proposed MC-SCCs. Our comparisons show that, under the constraint of equal decoding latency, a performance gain of about 0.4 dB is obtained with MC-SCC when compared with the underlying SC-SCC. These results show the potential advantages of MC-SCC in streaming applications.
{"title":"Enhancing Spatially Coupled Serially Concatenated Codes via Multidimensional Coupling","authors":"Feng Wang, Chaojie Yang, H. Du, Shancheng Zhao","doi":"10.1109/ICCC56324.2022.10065783","DOIUrl":"https://doi.org/10.1109/ICCC56324.2022.10065783","url":null,"abstract":"The spatially coupled turbo-like codes (SC-TCs) provide a new way to trade-off the performances between the water-fall region and the error-floor region. As a subclass of SC-TCs, spatially coupled serially concatenated codes (SC-SCCs) admit good performances in the error-floor region. This paper is concerned with the construction of SC-SCCs with improved water-fall performances. Particularly, we present the multidimensionally coupled serially concatenated codes (MC-SCCs), in which multiple SC-SCCs are coupled together in a cyclic manner. Two different decoding schedules are presented for the proposed MC-SCCs. Our comparisons show that, under the constraint of equal decoding latency, a performance gain of about 0.4 dB is obtained with MC-SCC when compared with the underlying SC-SCC. These results show the potential advantages of MC-SCC in streaming applications.","PeriodicalId":263098,"journal":{"name":"2022 IEEE 8th International Conference on Computer and Communications (ICCC)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121928563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-09DOI: 10.1109/ICCC56324.2022.10065954
Dejun Gao, Lei Wang
Human activity recognition (HAR) plays an important role in many applications such as smart homes, healthcare services, and security monitoring. Recently, WiFi-based human activity recognition (HAR) is becoming increasingly popular due to its non-invasiveness. Most existing HAR works only use classification methods for activity recognition, without focusing on the start time and end time of actions. In this paper, we propose to use a detection method that predicts both the type of activity as well as its start and end times. For detection tasks, both global information and local information are essential for modeling and identifying various types of activities. Therefore, we propose a multi-scale convolution Transformer that is able to exploit local features of WiFi data more effectively using CNNs, while global features are captured with Transformer. In our experiments, the proposed model shows outstanding performance in indoor environment, with a weak micro F1 score of 98.37% and a strong micro F1 score of 92.81%.
{"title":"Multi-scale Convolution Transformer for Human Activity Detection","authors":"Dejun Gao, Lei Wang","doi":"10.1109/ICCC56324.2022.10065954","DOIUrl":"https://doi.org/10.1109/ICCC56324.2022.10065954","url":null,"abstract":"Human activity recognition (HAR) plays an important role in many applications such as smart homes, healthcare services, and security monitoring. Recently, WiFi-based human activity recognition (HAR) is becoming increasingly popular due to its non-invasiveness. Most existing HAR works only use classification methods for activity recognition, without focusing on the start time and end time of actions. In this paper, we propose to use a detection method that predicts both the type of activity as well as its start and end times. For detection tasks, both global information and local information are essential for modeling and identifying various types of activities. Therefore, we propose a multi-scale convolution Transformer that is able to exploit local features of WiFi data more effectively using CNNs, while global features are captured with Transformer. In our experiments, the proposed model shows outstanding performance in indoor environment, with a weak micro F1 score of 98.37% and a strong micro F1 score of 92.81%.","PeriodicalId":263098,"journal":{"name":"2022 IEEE 8th International Conference on Computer and Communications (ICCC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121000108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-09DOI: 10.1109/ICCC56324.2022.10066046
Dai Jia, Junli Jia
In the broadcast scenario, how to use feedback chan-nel is always a hot research topic. If receivers have independent feedback channel, it will waste a lot of frequency or time slot resources. Whereas, if all receivers share the same channel to transmit feedback message, a feedback storm will occur, which causes the transmitter to be unable to confirm which receiver has successfully received the information packet. In order to make use of receivers feedback message, in this paper, we propose a novel fountain codes based on superposition feedback. By analyzing the intensity of received superposition feedback signal, the probability of information packet can be recovered by all receivers is calculated, which can be used to adjust the selection probability of information packets. Simulation results show that the proposed fountain codes in broadcast scenario can significantly reduce the overhead compared to traditional fountain codes.
{"title":"Fountain Codes with Superposition Feedback","authors":"Dai Jia, Junli Jia","doi":"10.1109/ICCC56324.2022.10066046","DOIUrl":"https://doi.org/10.1109/ICCC56324.2022.10066046","url":null,"abstract":"In the broadcast scenario, how to use feedback chan-nel is always a hot research topic. If receivers have independent feedback channel, it will waste a lot of frequency or time slot resources. Whereas, if all receivers share the same channel to transmit feedback message, a feedback storm will occur, which causes the transmitter to be unable to confirm which receiver has successfully received the information packet. In order to make use of receivers feedback message, in this paper, we propose a novel fountain codes based on superposition feedback. By analyzing the intensity of received superposition feedback signal, the probability of information packet can be recovered by all receivers is calculated, which can be used to adjust the selection probability of information packets. Simulation results show that the proposed fountain codes in broadcast scenario can significantly reduce the overhead compared to traditional fountain codes.","PeriodicalId":263098,"journal":{"name":"2022 IEEE 8th International Conference on Computer and Communications (ICCC)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116540748","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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