Movable antenna (MA) has been recognized as a promising technology to enhance the performance of wireless communication and sensing by enabling antenna movement. Such a significant paradigm shift from conventional fixed antennas (FAs) to MAs offers tremendous new opportunities towards realizing more versatile, adaptive and efficient next-generation wireless networks such as 6G. In this paper, we provide a comprehensive tutorial on the fundamentals and advancements in the area of MA-empowered wireless networks. First, we overview the historical development and contemporary applications of MA technologies. Next, to characterize the continuous variation in wireless channels with respect to antenna position and/or orientation, we present new field-response channel models tailored for MAs, which are applicable to narrowband and wideband systems as well as far-field and near-field propagation conditions. Subsequently, we review the state-of-the-art architectures for implementing MAs and discuss their practical constraints. A general optimization framework is then formulated to fully exploit the spatial degrees of freedom (DoFs) in antenna movement for performance enhancement in wireless systems. In particular, we delve into two major design issues for MA systems. First, we address the intricate antenna movement optimization problem for various communication and/or sensing systems to maximize the performance gains achievable by MAs. Second, we deal with the challenging channel acquisition issue in MA systems for reconstructing the channel mapping between arbitrary antenna positions inside the transmitter and receiver regions. Moreover, we show existing prototypes developed for MA-aided communication/sensing and the experimental results based on them. Finally, the extension of MA design to other wireless systems and its synergy with other emerging wireless technologies are discussed. We also highlight promising research directions in this area to inspire future investigations.
{"title":"A Tutorial on Movable Antennas for Wireless Networks","authors":"Lipeng Zhu;Wenyan Ma;Weidong Mei;Yong Zeng;Qingqing Wu;Boyu Ning;Zhenyu Xiao;Xiaodan Shao;Jun Zhang;Rui Zhang","doi":"10.1109/COMST.2025.3546373","DOIUrl":"10.1109/COMST.2025.3546373","url":null,"abstract":"Movable antenna (MA) has been recognized as a promising technology to enhance the performance of wireless communication and sensing by enabling antenna movement. Such a significant paradigm shift from conventional fixed antennas (FAs) to MAs offers tremendous new opportunities towards realizing more versatile, adaptive and efficient next-generation wireless networks such as 6G. In this paper, we provide a comprehensive tutorial on the fundamentals and advancements in the area of MA-empowered wireless networks. First, we overview the historical development and contemporary applications of MA technologies. Next, to characterize the continuous variation in wireless channels with respect to antenna position and/or orientation, we present new field-response channel models tailored for MAs, which are applicable to narrowband and wideband systems as well as far-field and near-field propagation conditions. Subsequently, we review the state-of-the-art architectures for implementing MAs and discuss their practical constraints. A general optimization framework is then formulated to fully exploit the spatial degrees of freedom (DoFs) in antenna movement for performance enhancement in wireless systems. In particular, we delve into two major design issues for MA systems. First, we address the intricate antenna movement optimization problem for various communication and/or sensing systems to maximize the performance gains achievable by MAs. Second, we deal with the challenging channel acquisition issue in MA systems for reconstructing the channel mapping between arbitrary antenna positions inside the transmitter and receiver regions. Moreover, we show existing prototypes developed for MA-aided communication/sensing and the experimental results based on them. Finally, the extension of MA design to other wireless systems and its synergy with other emerging wireless technologies are discussed. We also highlight promising research directions in this area to inspire future investigations.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"28 ","pages":"3002-3054"},"PeriodicalIF":34.4,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143518830","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}
Pub Date : 2025-02-25DOI: 10.1109/COMST.2025.3545541
Yebo Feng;Jun Li;Jelena Mirkovic;Cong Wu;Chong Wang;Hao Ren;Jiahua Xu;Yang Liu
Fine-grained traffic analysis (FGTA), as an advanced form of traffic analysis (TA), aims to analyze network traffic to deduce fine-grained information on or above the application layer, such as application-layer activities, fine-grained user behavior, or message content, even in the presence of traffic encryption or traffic obfuscation. Different from traditional TA, FGTA approaches are usually based on complicated processing pipelines or sophisticated data mining techniques such as deep learning or high-dimensional clustering, enabling them to discover subtle differences between different network traffic groups. Nowadays, with the increasingly complex Internet architecture, the increasingly frequent transmission of user data, and the widespread use of traffic encryption, FGTA is becoming an essential tool for both network administrators and attackers to gain different levels of visibility over the network. It plays a critical role in intrusion and anomaly detection, quality of experience investigation, user activity inference, website fingerprinting, location estimation, etc. To help scholars and developers research and advance this technology, in this survey paper, we examine the literature that deals with FGTA, investigating the frontier developments in this domain. By comprehensively surveying different approaches toward FGTA, we introduce their input traffic data, elaborate on their operating principles by different use cases, indicate their limitations and countermeasures, and raise several promising future research avenues.
{"title":"Unmasking the Internet: A Survey of Fine-Grained Network Traffic Analysis","authors":"Yebo Feng;Jun Li;Jelena Mirkovic;Cong Wu;Chong Wang;Hao Ren;Jiahua Xu;Yang Liu","doi":"10.1109/COMST.2025.3545541","DOIUrl":"10.1109/COMST.2025.3545541","url":null,"abstract":"Fine-grained traffic analysis (FGTA), as an advanced form of traffic analysis (TA), aims to analyze network traffic to deduce fine-grained information on or above the application layer, such as application-layer activities, fine-grained user behavior, or message content, even in the presence of traffic encryption or traffic obfuscation. Different from traditional TA, FGTA approaches are usually based on complicated processing pipelines or sophisticated data mining techniques such as deep learning or high-dimensional clustering, enabling them to discover subtle differences between different network traffic groups. Nowadays, with the increasingly complex Internet architecture, the increasingly frequent transmission of user data, and the widespread use of traffic encryption, FGTA is becoming an essential tool for both network administrators and attackers to gain different levels of visibility over the network. It plays a critical role in intrusion and anomaly detection, quality of experience investigation, user activity inference, website fingerprinting, location estimation, etc. To help scholars and developers research and advance this technology, in this survey paper, we examine the literature that deals with FGTA, investigating the frontier developments in this domain. By comprehensively surveying different approaches toward FGTA, we introduce their input traffic data, elaborate on their operating principles by different use cases, indicate their limitations and countermeasures, and raise several promising future research avenues.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 6","pages":"3672-3709"},"PeriodicalIF":34.4,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143495429","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}
Pub Date : 2025-02-25DOI: 10.1109/COMST.2025.3546166
Morteza Alijani;Cedric De Cock;Wout Joseph;David Plets
The latest advancements in visible light communication (VLC) technology have greatly facilitated the evolution of wireless sensing based on visible light, commonly referred to as visible light sensing (VLS) systems. Similar to other wireless sensing technologies, these systems can be categorized into two primary types: device-based (or active) and device-free (or passive), depending on whether targets, such as people or objects of interest, are equipped with an optical receiver (e.g., a photodiode or camera). By reusing the existing Light-emitting diode (LED) lighting infrastructure as transmitters in indoor environments, device-free VLS (DF-VLS) systems can help address the growing energy demands of ubiquitous sensing and communication in Sixth-Generation Wireless Networks (6G). This survey meticulously explores the landscape of DF-VLS technology, proposing a redefinition of the classification of VLS systems and delving into the existing literature in this domain. We conduct a comprehensive analysis of various DF-VLS sensing techniques, focusing on their diverse applications in the Internet of Things (IoT). By closely examining the integration and utility of DF-VLS in IoT environments, we highlight the potential of this technology. Furthermore, we underscore critical open challenges that demand attention for the effective development of efficient DF-VLS systems. Finally, the paper outlines a future roadmap for DF-VLS systems, shedding light on potential directions this field may embark upon.
{"title":"Device-Free Visible Light Sensing: A Survey","authors":"Morteza Alijani;Cedric De Cock;Wout Joseph;David Plets","doi":"10.1109/COMST.2025.3546166","DOIUrl":"10.1109/COMST.2025.3546166","url":null,"abstract":"The latest advancements in visible light communication (VLC) technology have greatly facilitated the evolution of wireless sensing based on visible light, commonly referred to as visible light sensing (VLS) systems. Similar to other wireless sensing technologies, these systems can be categorized into two primary types: device-based (or active) and device-free (or passive), depending on whether targets, such as people or objects of interest, are equipped with an optical receiver (e.g., a photodiode or camera). By reusing the existing Light-emitting diode (LED) lighting infrastructure as transmitters in indoor environments, device-free VLS (DF-VLS) systems can help address the growing energy demands of ubiquitous sensing and communication in Sixth-Generation Wireless Networks (6G). This survey meticulously explores the landscape of DF-VLS technology, proposing a redefinition of the classification of VLS systems and delving into the existing literature in this domain. We conduct a comprehensive analysis of various DF-VLS sensing techniques, focusing on their diverse applications in the Internet of Things (IoT). By closely examining the integration and utility of DF-VLS in IoT environments, we highlight the potential of this technology. Furthermore, we underscore critical open challenges that demand attention for the effective development of efficient DF-VLS systems. Finally, the paper outlines a future roadmap for DF-VLS systems, shedding light on potential directions this field may embark upon.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"28 ","pages":"3791-3829"},"PeriodicalIF":34.4,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10904171","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143495433","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}
Pub Date : 2025-02-18DOI: 10.1109/COMST.2025.3543197
Carlo Mazzocca;Abbas Acar;Selcuk Uluagac;Rebecca Montanari;Paolo Bellavista;Mauro Conti
Digital identity has always been one of the keystones for implementing secure and trustworthy communications among parties. The ever-evolving digital landscape has undergone numerous technological transformations that have profoundly reshaped digital identity management, leading to a major shift from centralized to decentralized identity models. The latest stage of this evolution is represented by the emerging paradigm of Self-Sovereign Identity (SSI), which gives identity owners full control over their data. SSI leverages Decentralized Identifiers (DIDs) and Verifiable Credentials (VCs), which have been recently standardized by the World Wide Web Consortium (W3C). These technologies have the potential to build more secure and decentralized digital identity systems, significantly strengthening communication security in scenarios involving many distributed participants. It is worth noting that use of DIDs and VCs is not limited to individuals but extends to a wide range of entities including cloud, edge, and Internet of Things (IoT) resources. However, due to their novelty, existing literature lacks a comprehensive survey on DIDs and VCs beyond the scope of SSI. This paper fills this gap by providing a comprehensive overview of DIDs and VCs from multiple perspectives. It identifies key security threats and mitigation strategies, analyzes available implementations to guide practitioners in making informed decisions, and reviews the adoption of these technologies across various application domains. Moreover, it also examines related regulations, projects, and consortiums emerging worldwide. Finally, it discusses the primary challenges hindering their real-world adoption and outlines future research directions.
{"title":"A Survey on Decentralized Identifiers and Verifiable Credentials","authors":"Carlo Mazzocca;Abbas Acar;Selcuk Uluagac;Rebecca Montanari;Paolo Bellavista;Mauro Conti","doi":"10.1109/COMST.2025.3543197","DOIUrl":"10.1109/COMST.2025.3543197","url":null,"abstract":"Digital identity has always been one of the keystones for implementing secure and trustworthy communications among parties. The ever-evolving digital landscape has undergone numerous technological transformations that have profoundly reshaped digital identity management, leading to a major shift from centralized to decentralized identity models. The latest stage of this evolution is represented by the emerging paradigm of Self-Sovereign Identity (SSI), which gives identity owners full control over their data. SSI leverages Decentralized Identifiers (DIDs) and Verifiable Credentials (VCs), which have been recently standardized by the World Wide Web Consortium (W3C). These technologies have the potential to build more secure and decentralized digital identity systems, significantly strengthening communication security in scenarios involving many distributed participants. It is worth noting that use of DIDs and VCs is not limited to individuals but extends to a wide range of entities including cloud, edge, and Internet of Things (IoT) resources. However, due to their novelty, existing literature lacks a comprehensive survey on DIDs and VCs beyond the scope of SSI. This paper fills this gap by providing a comprehensive overview of DIDs and VCs from multiple perspectives. It identifies key security threats and mitigation strategies, analyzes available implementations to guide practitioners in making informed decisions, and reviews the adoption of these technologies across various application domains. Moreover, it also examines related regulations, projects, and consortiums emerging worldwide. Finally, it discusses the primary challenges hindering their real-world adoption and outlines future research directions.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 6","pages":"3641-3671"},"PeriodicalIF":34.4,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143443625","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}
Pub Date : 2025-02-17DOI: 10.1109/COMST.2025.3542467
Qinwen Deng;Yao Ge;Zhi Ding
High mobility environment leads to severe Doppler effects and poses serious challenges to the conventional physical layer based on the widely popular orthogonal frequency division multiplexing (OFDM). The recent emergence of orthogonal time frequency space (OTFS) modulation, along with its many related variants, presents a promising solution to overcome such channel Doppler effects. This paper aims to clearly establish the relationships among the various manifestations of OTFS. Among these related modulations, we identify their connections, common features, and distinctions. Building on existing works, this work provides a general overview of various OTFS-related detection schemes and performance comparisons. We first provide an overview of OFDM and filter bank multi-carrier (FBMC) by demonstrating OTFS as a precoded FBMC through the introduction of inverse symplectic finite Fourier transform (ISFFT). We explore the relationship between OTFS and related modulation schemes with similar characteristics. We provide an effective channel model for high-mobility channels and offer a unified detection representation. We provide numerical comparisons of power spectrum density (PSD) and bit error rate (BER) to underscore the benefit of these modulation schemes in high-mobility scenarios. We also evaluate various detection schemes, revealing insights into their efficacies. We discuss opportunities and challenges for OTFS in high mobility, setting the stage for future research and development in this field.
{"title":"A Unifying View of OTFS and Its Many Variants","authors":"Qinwen Deng;Yao Ge;Zhi Ding","doi":"10.1109/COMST.2025.3542467","DOIUrl":"10.1109/COMST.2025.3542467","url":null,"abstract":"High mobility environment leads to severe Doppler effects and poses serious challenges to the conventional physical layer based on the widely popular orthogonal frequency division multiplexing (OFDM). The recent emergence of orthogonal time frequency space (OTFS) modulation, along with its many related variants, presents a promising solution to overcome such channel Doppler effects. This paper aims to clearly establish the relationships among the various manifestations of OTFS. Among these related modulations, we identify their connections, common features, and distinctions. Building on existing works, this work provides a general overview of various OTFS-related detection schemes and performance comparisons. We first provide an overview of OFDM and filter bank multi-carrier (FBMC) by demonstrating OTFS as a precoded FBMC through the introduction of inverse symplectic finite Fourier transform (ISFFT). We explore the relationship between OTFS and related modulation schemes with similar characteristics. We provide an effective channel model for high-mobility channels and offer a unified detection representation. We provide numerical comparisons of power spectrum density (PSD) and bit error rate (BER) to underscore the benefit of these modulation schemes in high-mobility scenarios. We also evaluate various detection schemes, revealing insights into their efficacies. We discuss opportunities and challenges for OTFS in high mobility, setting the stage for future research and development in this field.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 6","pages":"3561-3586"},"PeriodicalIF":34.4,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143443632","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}
In this survey paper, we present an extensive review of the use of reconfigurable intelligent surfaces (RIS) in 6G radio localization, highlighting their pivotal role as a low-cost, energy-efficient technology that reshapes wireless communication and localization landscapes. Investigating the versatile capabilities of RIS, we explore their dynamic control over electromagnetic wave manipulation, including reflection, refraction, and transmission, which opens new horizons in diverse applications ranging from Internet of Things (IoT) connectivity to advanced mobile communication, and various innovative applications in Industry 4.0. Our comprehensive review provides an overview of RIS use in 6G radio localization, highlighting recent progress in RIS technology assisted localization. It focuses on key aspects, including network scenarios, transmission bands, deployment environments, and near-field operations. We discuss studies to examine the state-of-the-art RIS-assisted localization and optimization techniques and their performance evaluation matrices. In addition, we present a detailed taxonomy of RIS-assisted radio localization, emphasizing the rapid evolution and potential of RIS technology in non-line-of-sight scenarios as an alternative to traditional base stations. Based on the careful investigation of the reviewed studies, the survey also sheds light on future research directions, technical challenges, and limitations, offering a clear perspective on the integration and optimization of RIS in 6G networks for enhanced localization capabilities.
{"title":"Reconfigurable Intelligent Surfaces in 6G Radio Localization: A Survey of Recent Developments, Opportunities, and Challenges","authors":"Anum Umer;Ivo Müürsepp;Muhammad Mahtab Alam;Henk Wymeersch","doi":"10.1109/COMST.2025.3536517","DOIUrl":"10.1109/COMST.2025.3536517","url":null,"abstract":"In this survey paper, we present an extensive review of the use of reconfigurable intelligent surfaces (RIS) in 6G radio localization, highlighting their pivotal role as a low-cost, energy-efficient technology that reshapes wireless communication and localization landscapes. Investigating the versatile capabilities of RIS, we explore their dynamic control over electromagnetic wave manipulation, including reflection, refraction, and transmission, which opens new horizons in diverse applications ranging from Internet of Things (IoT) connectivity to advanced mobile communication, and various innovative applications in Industry 4.0. Our comprehensive review provides an overview of RIS use in 6G radio localization, highlighting recent progress in RIS technology assisted localization. It focuses on key aspects, including network scenarios, transmission bands, deployment environments, and near-field operations. We discuss studies to examine the state-of-the-art RIS-assisted localization and optimization techniques and their performance evaluation matrices. In addition, we present a detailed taxonomy of RIS-assisted radio localization, emphasizing the rapid evolution and potential of RIS technology in non-line-of-sight scenarios as an alternative to traditional base stations. Based on the careful investigation of the reviewed studies, the survey also sheds light on future research directions, technical challenges, and limitations, offering a clear perspective on the integration and optimization of RIS in 6G networks for enhanced localization capabilities.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 6","pages":"3526-3560"},"PeriodicalIF":34.4,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143071913","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}
Pub Date : 2025-01-28DOI: 10.1109/COMST.2025.3535554
Fahime Khoramnejad;Ekram Hossain
Next-generation (xG) wireless networks, with their complex and dynamic nature, present significant challenges to using traditional optimization techniques. Generative Artificial Intelligence (GAI) emerges as a powerful tool due to its unique strengths. Unlike traditional optimization techniques and other machine learning methods, GAI excels at learning from real-world network data, capturing its intricacies. This enables safe, offline exploration of various configurations and generation of diverse, unseen scenarios, empowering proactive, data-driven exploration and optimization for xG networks. Additionally, GAI’s scalability makes it ideal for large-scale xG networks. This paper surveys how GAI-based models unlock optimization opportunities in xG wireless networks. We begin by providing a review of GAI models and some of the major communication paradigms of xG (e.g., Sixth Generation) wireless networks. We then delve into exploring how GAI can be used to improve resource allocation and enhance overall network performance. Additionally, we briefly review the networking requirements for supporting GAI applications in xG wireless networks. The paper further discusses the key challenges and future research directions in leveraging GAI for network optimization. Finally, a case study demonstrates the application of a diffusion-based GAI model for load balancing, carrier aggregation, and backhauling optimization in non-terrestrial networks, a core technology of xG networks. This case study serves as a practical example of how the combination of reinforcement learning and GAI can be implemented to address real-world network optimization problems.
{"title":"Generative AI for the Optimization of Next-Generation Wireless Networks: Basics, State-of-the-Art, and Open Challenges","authors":"Fahime Khoramnejad;Ekram Hossain","doi":"10.1109/COMST.2025.3535554","DOIUrl":"10.1109/COMST.2025.3535554","url":null,"abstract":"Next-generation (xG) wireless networks, with their complex and dynamic nature, present significant challenges to using traditional optimization techniques. Generative Artificial Intelligence (GAI) emerges as a powerful tool due to its unique strengths. Unlike traditional optimization techniques and other machine learning methods, GAI excels at learning from real-world network data, capturing its intricacies. This enables safe, offline exploration of various configurations and generation of diverse, unseen scenarios, empowering proactive, data-driven exploration and optimization for xG networks. Additionally, GAI’s scalability makes it ideal for large-scale xG networks. This paper surveys how GAI-based models unlock optimization opportunities in xG wireless networks. We begin by providing a review of GAI models and some of the major communication paradigms of xG (e.g., Sixth Generation) wireless networks. We then delve into exploring how GAI can be used to improve resource allocation and enhance overall network performance. Additionally, we briefly review the networking requirements for supporting GAI applications in xG wireless networks. The paper further discusses the key challenges and future research directions in leveraging GAI for network optimization. Finally, a case study demonstrates the application of a diffusion-based GAI model for load balancing, carrier aggregation, and backhauling optimization in non-terrestrial networks, a core technology of xG networks. This case study serves as a practical example of how the combination of reinforcement learning and GAI can be implemented to address real-world network optimization problems.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 6","pages":"3483-3525"},"PeriodicalIF":34.4,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143055095","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}
In traditional centralized machine learning, transmitting raw data to a cloud center incurs high communication costs and raises privacy concerns. This is particularly challenging in mobile edge environments, where devices are dynamic and resource-constrained. Federated Learning (FL) addresses these issues by allowing devices to train models locally and upload parameters to a central server without sharing local data. However, limited wireless channel resources and dynamic transmission performance make communication overhead a major bottleneck of FL in mobile edge environments. Concerning this challenge, this survey provides a comprehensive summary of methods to improve communication efficiency in FL, focusing on: 1) minimizing communication complexity to reduce total transmission volume, 2) scheduling resources appropriately to improve training efficiency, 3) utilizing over-the-air computation (OTA) to integrate computation into communication for accommodating the computation/communication characteristics of FL in mobile edge environments. Thus, this work analyzes research from the perspective of convergence and data heterogeneity to reduce communication rounds by optimizing algorithm performance. We hope that this survey could offer insights into communication-efficient FL for future research.
{"title":"A Comprehensive Survey on Communication-Efficient Federated Learning in Mobile Edge Environments","authors":"Ninghui Jia;Zhihao Qu;Baoliu Ye;Yanyan Wang;Shihong Hu;Song Guo","doi":"10.1109/COMST.2025.3535957","DOIUrl":"10.1109/COMST.2025.3535957","url":null,"abstract":"In traditional centralized machine learning, transmitting raw data to a cloud center incurs high communication costs and raises privacy concerns. This is particularly challenging in mobile edge environments, where devices are dynamic and resource-constrained. Federated Learning (FL) addresses these issues by allowing devices to train models locally and upload parameters to a central server without sharing local data. However, limited wireless channel resources and dynamic transmission performance make communication overhead a major bottleneck of FL in mobile edge environments. Concerning this challenge, this survey provides a comprehensive summary of methods to improve communication efficiency in FL, focusing on: 1) minimizing communication complexity to reduce total transmission volume, 2) scheduling resources appropriately to improve training efficiency, 3) utilizing over-the-air computation (OTA) to integrate computation into communication for accommodating the computation/communication characteristics of FL in mobile edge environments. Thus, this work analyzes research from the perspective of convergence and data heterogeneity to reduce communication rounds by optimizing algorithm performance. We hope that this survey could offer insights into communication-efficient FL for future research.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 6","pages":"3710-3741"},"PeriodicalIF":34.4,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143055071","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}
Network virtualization (NV) allows service providers (SPs) to instantiate logically isolated entities called virtual networks (VNs) on top of a substrate network (SN). Though VNs bring about multiple benefits, particularly in terms of economic costs and elasticity, they also force various technical challenges to be addressed. The primary one is the issue of optimally allocating resources to VNs, also termed virtual network embedding (VNE). This paper presents an exhaustive survey of VNE by extensively covering the state-of-the-art research field in this very active field and focusing on the emerging research trends in industry and academia over the last decade. In addition, this survey originally contributes to the literature by proposing a novel taxonomy for existing VNE solutions and providing a thorough comparative study of their strategies.
{"title":"Virtual Network Embedding: Literature Assessment, Recent Advancements, Opportunities, and Challenges","authors":"Anurag Satpathy;Manmath Narayan Sahoo;Chittaranjan Swain;Paolo Bellavista;Mohsen Guizani;Khan Muhammad;Sambit Bakshi","doi":"10.1109/COMST.2025.3531724","DOIUrl":"10.1109/COMST.2025.3531724","url":null,"abstract":"Network virtualization (NV) allows service providers (SPs) to instantiate logically isolated entities called virtual networks (VNs) on top of a substrate network (SN). Though VNs bring about multiple benefits, particularly in terms of economic costs and elasticity, they also force various technical challenges to be addressed. The primary one is the issue of optimally allocating resources to VNs, also termed virtual network embedding (VNE). This paper presents an exhaustive survey of VNE by extensively covering the state-of-the-art research field in this very active field and focusing on the emerging research trends in industry and academia over the last decade. In addition, this survey originally contributes to the literature by proposing a novel taxonomy for existing VNE solutions and providing a thorough comparative study of their strategies.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 6","pages":"3861-3914"},"PeriodicalIF":34.4,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142991192","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}
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