IEEE Journal on Selected Areas in Communications最新文献_第10页

Soft Demapping of Spherical Codes from Cartesian Powers of PAM Constellations PAM星座笛卡尔幂的球码软映射

IF 16.4 1区计算机科学

IEEE Journal on Selected Areas in Communications Pub Date : 2025-02-19 DOI: 10.1109/jsac.2025.3543495

Reza Rafie Borujeny, Susanna E. Rumsey, Stark C. Draper, Frank R. Kschischang

引用次数: 0

Employing Weak-Field Homodyne Detection for Optical Communications 利用弱场纯差检测进行光通信

IF 16.4 1区计算机科学

IEEE Journal on Selected Areas in Communications Pub Date : 2025-02-19 DOI: 10.1109/jsac.2025.3543497

Michele N. Notarnicola, Stefano Olivares

引用次数: 0

Information Rates of Successive Interference Cancellation for Optical Fiber 光纤连续干扰消除的信息率

IF 16.4 1区计算机科学

IEEE Journal on Selected Areas in Communications Pub Date : 2025-02-19 DOI: 10.1109/jsac.2025.3543543

Alex Jäger, Gerhard Kramer

引用次数: 0

Multi-Failure Localization in High-Degree ROADM-based Optical Networks using Rules-Informed Neural Networks 基于规则通知神经网络的高度roadm光网络多故障定位

IF 16.4 1区计算机科学

IEEE Journal on Selected Areas in Communications Pub Date : 2025-02-19 DOI: 10.1109/jsac.2025.3543482

Ruikun Wang, Qiaolun Zhang, Jiawei Zhang, Zhiqun Gu, Memedhe Ibrahimi, Hao Yu, Bojun Zhang, Francesco Musumeci, Yuefeng Ji, Massimo Tornatore

引用次数: 0

Mixed RF/FSO Communication Systems with Rate Splitting 具有速率分割的混合RF/FSO通信系统

IF 16.4 1区计算机科学

IEEE Journal on Selected Areas in Communications Pub Date : 2025-02-19 DOI: 10.1109/jsac.2025.3543529

Yiran Zhang, Zhichen Xiao, Liang Yang, Petros S. Bithas, Mazen O. Hasna, George K. Karagiannidis

引用次数: 0

Semantically-Disentangled Progressive Image Compression for Deep Space Communications: Exploring the Ultra-low Rate Regime 用于深空通信的语义分解逐行图像压缩：探索超低速率区

IF 16.4 1区计算机科学

IEEE Journal on Selected Areas in Communications Pub Date : 2024-02-26 DOI: 10.1109/jsac.2024.3365886

Weicheng Zhang, Yajing Liu, Lingyu Chen, Jianghong Shi, Xuemin Hong, Xianbin Wang

引用次数: 0

Safety and Efficacy of Autologous Cartilage Graft in Augmentation Rhinoplasty. 自体软骨移植在隆鼻手术中的安全性和有效性

IF 13.8 1区计算机科学

IEEE Journal on Selected Areas in Communications Pub Date : 2024-02-01 Epub Date: 2023-08-07 DOI: 10.1007/s12070-023-03999-5

Mahmoud Ahmed Shawky, Mohamed Ahmed Shawky, Nada Zakaria Zakaria

{"title":"Safety and Efficacy of Autologous Cartilage Graft in Augmentation Rhinoplasty.","authors":"Mahmoud Ahmed Shawky, Mohamed Ahmed Shawky, Nada Zakaria Zakaria","doi":"10.1007/s12070-023-03999-5","DOIUrl":"10.1007/s12070-023-03999-5","url":null,"abstract":"<p><p>Augmentation rhinoplasty or commonly known as \"nose jobs\" is one of the most common plastic surgical procedures aimed to improve cosmetic appearance. This procedure is considerably safer, less time consuming with faster recovery and immediate cosmetic effect. This procedure needs of highly experienced and well-trained plastic surgeon. According to facial analysis you can select the type of rhinoplasty. Open discussion with the patient to select appropriate surgical technique and its possible risks with your plastic surgeon to ensure the highest level of safety and satisfaction. Autologous grafting materials are safe, efficient and also the first choice for rhinoplasty due to it can survive without a vascular supply, the resorption rate of cartilage is much lower than that of a bone graft. Autologous grafting materials are stable and resistant to infection and extrusion over time so, they are successfully used for dorsal augmentation. To perform successful augmentation rhinoplasty, surgeons should be highly experienced and well-trained and augmentation materials that are currently available and understand their risks, benefits and uses. Autologous cartilage graft regarded as the graft of choice in augmentation rhinoplasty because of their lower rate of infection, rejection, resorption, extrusion, donor site morbidity, easy reshaping.</p>","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"24 1","pages":"19-25"},"PeriodicalIF":13.8,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10908760/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84350736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Towards Communication-efficient Digital Twin via AI-powered Transmission and Reconstruction 通过人工智能传输和重建实现高效通信的数字孪生

IF 16.4 1区计算机科学

IEEE Journal on Selected Areas in Communications Pub Date : 2023-11-01 DOI: 10.1109/jsac.2023.3310089

Mi Li, Cen Chen, Xulei Yang, Joey Tianyi Zhou, Tao Zhang, Yangfan Li

{"title":"Towards Communication-efficient Digital Twin via AI-powered Transmission and Reconstruction","authors":"Mi Li, Cen Chen, Xulei Yang, Joey Tianyi Zhou, Tao Zhang, Yangfan Li","doi":"10.1109/jsac.2023.3310089","DOIUrl":"https://doi.org/10.1109/jsac.2023.3310089","url":null,"abstract":"Digital twin technology has recently gathered pace in engineering communities as it allows for the convergence of the real structure and its digital counterpart. 3D point cloud data is a more effective way to describe the real world and to reconstruct the digital counterpart than the conventional 2D images or 360-degree images. Large-scale, e.g., city-scale digital twins, typically collect point cloud data via internet-of-things (IoT) devices and transmit it over wireless networks. However, the existing wireless transmission technology can not carry real-time point cloud transmission for digital twin reconstruction due to mass data volume, high processing overheads, and low delay-tolerance. We propose a novel artificial intelligence (AI) powered end-to-end framework, termed AIRec, for efficient digital twin communication from point cloud compression, wireless channel coding, and digital twin reconstruction. AIRec adopts the encoder-decoder architecture. In the encoder, a novel importance-aware pooling scheme is designed to adaptively select important points with learnable thresholds to reduce the transmission volume. We also design a novel noise-aware joint source and channel coding is proposed to adaptively adjust the transmission strategy based on SNR and map the features to error-resilient channel symbols for wireless transmission to achieve a good tradeoff between the transmission rate and reconstruction quality. The decoder can accurately reconstruct the digital twins from the received symbols. Extensive experiments of typical datasets and comparison with baselines show that we achieve a good reconstruction quality under $24times $ compression ratio.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"1 1","pages":"3624-3635"},"PeriodicalIF":16.4,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62352333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Digital Twin-enabled Federated Learning in Mobile Networks: From the Perspective of Communication-assisted Sensing 移动网络中数字孪生支持的联邦学习:从通信辅助传感的角度

IF 16.4 1区计算机科学

IEEE Journal on Selected Areas in Communications Pub Date : 2023-10-01 DOI: 10.1109/jsac.2023.3310082

Junsheng Mu, Wenjia Ouyang, Tao Hong, Weijie Yuan, Yuanhao Cui, Zexuan Jing

{"title":"Digital Twin-enabled Federated Learning in Mobile Networks: From the Perspective of Communication-assisted Sensing","authors":"Junsheng Mu, Wenjia Ouyang, Tao Hong, Weijie Yuan, Yuanhao Cui, Zexuan Jing","doi":"10.1109/jsac.2023.3310082","DOIUrl":"https://doi.org/10.1109/jsac.2023.3310082","url":null,"abstract":"With the continuous evolution of emerging technologies such as mobile network, machine learning (ML), 5G, etc., digital twins (DT) bursts out great potential by its capacity of data analysis, data tracking, data prediction, etc, building a bridge between the physical and information world. Meanwhile, mobile network is moving towards data-driven paradigm, the issue of data privacy and data security seem to be a bottleneck. As a result, federated learning (FL) and mobile network are deeply converging. However, the mobile network is time-varying and the parameters of FL-empowered mobile network is huge and continue to increase with exponential growth of wireless terminals, result in the failure of traditional modeling. In the mobile networks, DT is conducive to prototyping, testing, and optimization, enabling mobile networks to be modelled more efficiently in a virtual environment and thus providing guidance for practical application. To this end, a communication-assisted sensing scenario is considered in this paper with FL in DT-empowered mobile networks. More specifically, two communication-assisted sensing architectures are proposed to improve communication efficiency of mobile network, namely, centralized architecture of federated transfer learning (FTL) and decentralized architecture of FTL. For centralized architecture of FTL, feature extraction of sensing information is conducted by FL between partial nodes and central server while the remaining nodes are used to train the fully connected layers at the central server. Considering data safety during the communication between sensing nodes, a decentralized architecture is designed based on FTL and Blockchain, where the feature extraction module is obtained by the fusion of sharing model (by Blockchain) and local model. The performance of proposed schemes is evaluated and demonstrated by the simulations.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"25 1","pages":"3230-3241"},"PeriodicalIF":16.4,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62352164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Joint Device Selection and Power Control for Wireless Federated Learning 无线联邦学习的联合设备选择和功率控制

IF 16.4 1区计算机科学

IEEE Journal on Selected Areas in Communications Pub Date : 2022-05-19 DOI: 10.48550/arXiv.2205.09306

Weihua Guo, Ran Li, Chuan Huang, Xiaoqi Qin, Kaiming Shen, Wei Zhang

{"title":"Joint Device Selection and Power Control for Wireless Federated Learning","authors":"Weihua Guo, Ran Li, Chuan Huang, Xiaoqi Qin, Kaiming Shen, Wei Zhang","doi":"10.48550/arXiv.2205.09306","DOIUrl":"https://doi.org/10.48550/arXiv.2205.09306","url":null,"abstract":"This paper studies the joint device selection and power control scheme for wireless federated learning (FL), considering both the downlink and uplink communications between the parameter server (PS) and the terminal devices. In each round of model training, the PS first broadcasts the global model to the terminal devices in an analog fashion, and then the terminal devices perform local training and upload the updated model parameters to the PS via over-the-air computation (AirComp). First, we propose an AirComp-based adaptive reweighing scheme for the aggregation of local updated models, where the model aggregation weights are directly determined by the uplink transmit power values of the selected devices and which enables the joint learning and communication optimization simply by the device selection and power control. Furthermore, we provide a convergence analysis for the proposed wireless FL algorithm and the upper bound on the expected optimality gap between the expected and optimal global loss values is derived. With instantaneous channel state information (CSI), we formulate the optimality gap minimization problems under both the individual and sum uplink transmit power constraints, respectively, which are shown to be solved by the semidefinite programming (SDR) technique. Numerical results reveal that our proposed wireless FL algorithm achieves close to the best performance by using the ideal FedAvg scheme with error-free model exchange and full device participation.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"40 1","pages":"2395-2410"},"PeriodicalIF":16.4,"publicationDate":"2022-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42679325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 22