Pub Date : 2025-06-03DOI: 10.1109/COMST.2025.3576289
G. M. Dotreppe;A. Mentens;J. Coosemans;P. Van den Bossche;V. A. Jacobs
Unlike radio-frequency (RF) systems, including Wi-Fi and cellular networks, which encounter interference, bandwidth limitations, network congestion, and security vulnerabilities, Vehicular Visible Light Communication (V-VLC) offers a compelling alternative as a communication medium. Its unlicensed spectrum, extensive bandwidth, energy efficiency, and existing transmitters render it a promising option for vehicular communication in the context of Intelligent Transportation Systems. By integrating V-VLC with traditional RF communication systems, a vast ecosystem of interconnected vehicles can be realised, thereby enhancing safety and efficiency for future fleets of (autonomous) vehicles. Despite successful integration of VLC in indoor environments, further investigation is required for outdoor applications. This study examines current channel modelling approaches for V-VLC within the framework of Intelligent Transportation Systems. Through a review of the literature within the period between 2013 and 2024 the advancements of V-VLC as a valuable addition to vehicular networks, with a specific emphasis on photometric aspects of the optical channel models, are assessed.
{"title":"Shedding Light on Vehicular Communication: A Review of the Latest Vehicular Visible Light Communication Channel Models","authors":"G. M. Dotreppe;A. Mentens;J. Coosemans;P. Van den Bossche;V. A. Jacobs","doi":"10.1109/COMST.2025.3576289","DOIUrl":"10.1109/COMST.2025.3576289","url":null,"abstract":"Unlike radio-frequency (RF) systems, including Wi-Fi and cellular networks, which encounter interference, bandwidth limitations, network congestion, and security vulnerabilities, Vehicular Visible Light Communication (V-VLC) offers a compelling alternative as a communication medium. Its unlicensed spectrum, extensive bandwidth, energy efficiency, and existing transmitters render it a promising option for vehicular communication in the context of Intelligent Transportation Systems. By integrating V-VLC with traditional RF communication systems, a vast ecosystem of interconnected vehicles can be realised, thereby enhancing safety and efficiency for future fleets of (autonomous) vehicles. Despite successful integration of VLC in indoor environments, further investigation is required for outdoor applications. This study examines current channel modelling approaches for V-VLC within the framework of Intelligent Transportation Systems. Through a review of the literature within the period between 2013 and 2024 the advancements of V-VLC as a valuable addition to vehicular networks, with a specific emphasis on photometric aspects of the optical channel models, are assessed.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"28 ","pages":"3165-3194"},"PeriodicalIF":34.4,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144210802","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}
The Internet of Everything (IoE) integrates people, processes, data, and things into a unified network, enabling highly interconnected systems with enhanced performance in terms of delay, reliability, and connection density. With the advent of next-generation networks, IoE has garnered significant attention for its transformative potential across various domains. However, while most existing studies focus on developing enabling technologies and deployment frameworks, the economic dimensions of IoE systems remain critically underexplored, despite being essential for ensuring their sustainability and scalability. This paper addresses this gap by providing a comprehensive review of the economic analysis of IoE systems. Specifically, we categorize existing research into four key aspects: information collection, information transmission, information fusion, and service application. We identify major economic challenges and propose modeling approaches, including game-theoretic and learning-based methods. Furthermore, we explore diverse IoE application scenarios, such as metaverse solutions and large-scale industrial systems, and summarize prevailing business patterns in the industry. By highlighting the economic dimension as a core component of IoE systems, this survey offers valuable insights into future research directions and outlines critical open challenges.
万物互联（Internet of Everything, IoE）是指将人、流程、数据和事物整合到一个统一的网络中，实现高度互联的系统，在时延、可靠性和连接密度等方面实现更高的性能。随着下一代网络的出现，物联网因其在各个领域的变革潜力而获得了极大的关注。然而，尽管大多数现有研究都集中在开发使能技术和部署框架上，但物联网系统的经济维度仍未得到充分探索，尽管这对确保其可持续性和可扩展性至关重要。本文通过对物联网系统的经济分析进行全面回顾，解决了这一差距。具体而言，我们将现有的研究分为四个关键方面：信息收集、信息传输、信息融合和服务应用。我们确定了主要的经济挑战并提出了建模方法，包括博弈论和基于学习的方法。此外，我们还探索了不同的物联网应用场景，如元宇宙解决方案和大规模工业系统，并总结了行业中流行的业务模式。通过强调经济维度作为物联网系统的核心组成部分，本调查为未来的研究方向提供了有价值的见解，并概述了关键的开放挑战。
{"title":"An Overview on Economic Analysis of Internet of Everything","authors":"Ningning Ding;Xiaomin Ouyang;Lin Gao;Jianwei Huang;Guoliang Xing","doi":"10.1109/COMST.2025.3556999","DOIUrl":"10.1109/COMST.2025.3556999","url":null,"abstract":"The Internet of Everything (IoE) integrates people, processes, data, and things into a unified network, enabling highly interconnected systems with enhanced performance in terms of delay, reliability, and connection density. With the advent of next-generation networks, IoE has garnered significant attention for its transformative potential across various domains. However, while most existing studies focus on developing enabling technologies and deployment frameworks, the economic dimensions of IoE systems remain critically underexplored, despite being essential for ensuring their sustainability and scalability. This paper addresses this gap by providing a comprehensive review of the economic analysis of IoE systems. Specifically, we categorize existing research into four key aspects: information collection, information transmission, information fusion, and service application. We identify major economic challenges and propose modeling approaches, including game-theoretic and learning-based methods. Furthermore, we explore diverse IoE application scenarios, such as metaverse solutions and large-scale industrial systems, and summarize prevailing business patterns in the industry. By highlighting the economic dimension as a core component of IoE systems, this survey offers valuable insights into future research directions and outlines critical open challenges.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 6","pages":"3742-3771"},"PeriodicalIF":34.4,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143775458","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 : 2025-03-25DOI: 10.1109/COMST.2025.3554579
Ruhan Liu;Tom H. Luan;Youyang Qu;Yong Xiang;Longxiang Gao;Dongmei Zhao
Intelligent physical systems, such as smart vehicles and robotic arms, are increasingly integrated into both industrial and everyday applications. However, the systems typically face hardware limitations that constrain their computational capacities. Digital twin systems offer a solution by creating real-time digital replicas of physical systems that enhance computational efficiency, overcoming physical limitations. Moreover, multiple digital twins that hold complementary knowledge can conveniently collaborate to share information and computational resources, further improving the performance of physical systems by forming an Internet of Digital Twin (IoDT). This paper presents a comprehensive investigation of the digital twin network, tracing the evolution of digital twins and providing a classification of the key technologies, functional frameworks, and application domains of IoDT. This paper delves into the IoDT communication framework by studying the fundamental communication modes of IoDT, exploring its integration with advanced technologies such as edge computing, blockchain, 5G/6G networks, and machine learning to facilitate data transmission, interaction, and omni-directional sensing. By offering a broad perspective, the paper aims to deepen stakeholders’ understanding of current research and potential future developments, encouraging further exploration of IoDT technologies and their evolution.
智能物理系统，如智能车辆和机械臂，越来越多地集成到工业和日常应用中。然而，这些系统通常面临硬件限制，限制了它们的计算能力。数字孪生系统通过创建物理系统的实时数字副本来提供解决方案，从而提高计算效率，克服物理限制。此外，拥有互补知识的多个数字孪生可以方便地协作共享信息和计算资源，通过形成数字孪生互联网（Internet of digital Twin, IoDT）进一步提高物理系统的性能。本文对数字孪生网络进行了全面的研究，追溯了数字孪生网络的发展历程，并对数字孪生网络的关键技术、功能框架和应用领域进行了分类。本文通过研究IoDT的基本通信模式，深入研究IoDT通信框架，探索其与边缘计算、区块链、5G/6G网络、机器学习等先进技术的融合，促进数据传输、交互和全方位感知。通过提供一个广阔的视角，本文旨在加深利益相关者对当前研究和潜在未来发展的理解，鼓励进一步探索碘替代技术及其发展。
{"title":"Internet of Digital Twin: Framework, Applications, and Enabling Technologies","authors":"Ruhan Liu;Tom H. Luan;Youyang Qu;Yong Xiang;Longxiang Gao;Dongmei Zhao","doi":"10.1109/COMST.2025.3554579","DOIUrl":"10.1109/COMST.2025.3554579","url":null,"abstract":"Intelligent physical systems, such as smart vehicles and robotic arms, are increasingly integrated into both industrial and everyday applications. However, the systems typically face hardware limitations that constrain their computational capacities. Digital twin systems offer a solution by creating real-time digital replicas of physical systems that enhance computational efficiency, overcoming physical limitations. Moreover, multiple digital twins that hold complementary knowledge can conveniently collaborate to share information and computational resources, further improving the performance of physical systems by forming an Internet of Digital Twin (IoDT). This paper presents a comprehensive investigation of the digital twin network, tracing the evolution of digital twins and providing a classification of the key technologies, functional frameworks, and application domains of IoDT. This paper delves into the IoDT communication framework by studying the fundamental communication modes of IoDT, exploring its integration with advanced technologies such as edge computing, blockchain, 5G/6G networks, and machine learning to facilitate data transmission, interaction, and omni-directional sensing. By offering a broad perspective, the paper aims to deepen stakeholders’ understanding of current research and potential future developments, encouraging further exploration of IoDT technologies and their evolution.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"28 ","pages":"3870-3910"},"PeriodicalIF":34.4,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143702647","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}
The use of autonomous aerial vehicles (AAVs) for a variety of commercial, civilian, and defense applications has increased many folds in recent years. While AAVs are expected to transform future air operations, there are instances where they can be used for malicious purposes. In this context, the detection, classification, and tracking (DCT) of AAVs (DCT-U) for safety and surveillance of national air space is a challenging task when compared to DCT of manned aerial vehicles. In this survey, we discuss the threats and challenges from malicious AAVs and we subsequently study three radio frequency (RF)-based systems for DCT-U. These RF-based systems include radars, communication systems, and RF analyzers. Radar systems are further divided into conventional and modern radar systems, while communication systems can be used for joint communications and sensing (JC&S) in active mode and act as a source of illumination to passive radars for DCT-U. The limitations of the three RF-based systems are also provided. The survey briefly discusses non-RF systems for DCT-U and their limitations. Future directions based on the lessons learned are provided at the end of the survey.
{"title":"A Survey on Detection, Classification, and Tracking of AAVs Using Radar and Communications Systems","authors":"Wahab Khawaja;Martins Ezuma;Vasilii Semkin;Fatih Erden;Ozgur Ozdemir;Ismail Guvenc","doi":"10.1109/COMST.2025.3554613","DOIUrl":"10.1109/COMST.2025.3554613","url":null,"abstract":"The use of autonomous aerial vehicles (AAVs) for a variety of commercial, civilian, and defense applications has increased many folds in recent years. While AAVs are expected to transform future air operations, there are instances where they can be used for malicious purposes. In this context, the detection, classification, and tracking (DCT) of AAVs (DCT-U) for safety and surveillance of national air space is a challenging task when compared to DCT of manned aerial vehicles. In this survey, we discuss the threats and challenges from malicious AAVs and we subsequently study three radio frequency (RF)-based systems for DCT-U. These RF-based systems include radars, communication systems, and RF analyzers. Radar systems are further divided into conventional and modern radar systems, while communication systems can be used for joint communications and sensing (JC&S) in active mode and act as a source of illumination to passive radars for DCT-U. The limitations of the three RF-based systems are also provided. The survey briefly discusses non-RF systems for DCT-U and their limitations. Future directions based on the lessons learned are provided at the end of the survey.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"28 ","pages":"3272-3310"},"PeriodicalIF":34.4,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143702838","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 : 2025-03-15DOI: 10.1109/COMST.2025.3570288
Minh K. Quan;Pubudu N. Pathirana;Mayuri Wijayasundara;Sujeeva Setunge;Dinh C. Nguyen;Christopher G. Brinton;David J. Love;H. Vincent Poor
The integration of machine learning (ML) in cyber physical systems (CPS) is a complex task due to the challenges that arise in terms of real-time decision making, safety, reliability, device heterogeneity, and data privacy. There are also open research questions that must be addressed in order to fully realize the potential of ML in CPS. Federated learning (FL), a distributed approach to ML, has become increasingly popular in recent years. It allows models to be trained using data from decentralized sources. This approach has been gaining popularity in the CPS field, as it integrates computer, communication, and physical processes. Therefore, the purpose of this work is to provide a comprehensive analysis of the most recent developments of FL-CPS, including the numerous application areas, system topologies, and algorithms developed in recent years. The paper starts by discussing recent advances in both FL and CPS, followed by their integration. Then, the paper compares the application of FL in CPS with its applications in the Internet of Things (IoT) in further depth to show their connections and distinctions. Furthermore, the article scrutinizes how FL is utilized in critical CPS applications, e.g., intelligent transportation systems, cybersecurity services, smart cities, and smart healthcare solutions. The study also includes critical insights and lessons learned from various FL-CPS implementations. The paper’s concluding section delves into significant concerns and suggests avenues for further research in this fast-paced and dynamic era.
{"title":"Federated Learning for Cyber Physical Systems: A Comprehensive Survey","authors":"Minh K. Quan;Pubudu N. Pathirana;Mayuri Wijayasundara;Sujeeva Setunge;Dinh C. Nguyen;Christopher G. Brinton;David J. Love;H. Vincent Poor","doi":"10.1109/COMST.2025.3570288","DOIUrl":"10.1109/COMST.2025.3570288","url":null,"abstract":"The integration of machine learning (ML) in cyber physical systems (CPS) is a complex task due to the challenges that arise in terms of real-time decision making, safety, reliability, device heterogeneity, and data privacy. There are also open research questions that must be addressed in order to fully realize the potential of ML in CPS. Federated learning (FL), a distributed approach to ML, has become increasingly popular in recent years. It allows models to be trained using data from decentralized sources. This approach has been gaining popularity in the CPS field, as it integrates computer, communication, and physical processes. Therefore, the purpose of this work is to provide a comprehensive analysis of the most recent developments of FL-CPS, including the numerous application areas, system topologies, and algorithms developed in recent years. The paper starts by discussing recent advances in both FL and CPS, followed by their integration. Then, the paper compares the application of FL in CPS with its applications in the Internet of Things (IoT) in further depth to show their connections and distinctions. Furthermore, the article scrutinizes how FL is utilized in critical CPS applications, e.g., intelligent transportation systems, cybersecurity services, smart cities, and smart healthcare solutions. The study also includes critical insights and lessons learned from various FL-CPS implementations. The paper’s concluding section delves into significant concerns and suggests avenues for further research in this fast-paced and dynamic era.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"28 ","pages":"3751-3790"},"PeriodicalIF":34.4,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144066165","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}
Wireless signal recognition (WSR) is a crucial technique for intelligent communications and spectrum sharing in the next six-generation (6G) wireless communication networks. It can be utilized to enhance network performance and efficiency, improve quality of service (QoS), and improve network security and reliability. Additionally, WSR can be applied for military applications such as signal interception, signal race, and signal abduction. In the past decades, great efforts have been made for the research of WSR. Earlier works mainly focus on model-based methods, including likelihood-based (LB) and feature-based (FB) methods, which have taken the leading position for many years. With the emergence of artificial intelligence (AI), intelligent methods including machine learning-based (ML-based) and deep learning-based (DL-based) methods have been developed to extract the features of the received signals and perform the classification. In this work, we provide a comprehensive review of WSR from the view of applications, main tasks, recent advances, datasets and evaluation metrics, challenges, and future directions. Specifically, intelligent WSR methods are introduced from the perspective of model, data, learning and implementation. Moreover, we analyze the challenges for WSR from the view of complex, dynamic, and open 6G wireless environments and discuss the future directions for WSR. This survey is expected to provide a comprehensive overview of the state-of-the-art WSR techniques and inspire new research directions for WSR in 6G networks.
{"title":"Revolution of Wireless Signal Recognition for 6G: Recent Advances, Challenges and Future Directions","authors":"Hao Zhang;Fuhui Zhou;Hongyang Du;Qihui Wu;Chau Yuen","doi":"10.1109/COMST.2025.3569427","DOIUrl":"10.1109/COMST.2025.3569427","url":null,"abstract":"Wireless signal recognition (WSR) is a crucial technique for intelligent communications and spectrum sharing in the next six-generation (6G) wireless communication networks. It can be utilized to enhance network performance and efficiency, improve quality of service (QoS), and improve network security and reliability. Additionally, WSR can be applied for military applications such as signal interception, signal race, and signal abduction. In the past decades, great efforts have been made for the research of WSR. Earlier works mainly focus on model-based methods, including likelihood-based (LB) and feature-based (FB) methods, which have taken the leading position for many years. With the emergence of artificial intelligence (AI), intelligent methods including machine learning-based (ML-based) and deep learning-based (DL-based) methods have been developed to extract the features of the received signals and perform the classification. In this work, we provide a comprehensive review of WSR from the view of applications, main tasks, recent advances, datasets and evaluation metrics, challenges, and future directions. Specifically, intelligent WSR methods are introduced from the perspective of model, data, learning and implementation. Moreover, we analyze the challenges for WSR from the view of complex, dynamic, and open 6G wireless environments and discuss the future directions for WSR. This survey is expected to provide a comprehensive overview of the state-of-the-art WSR techniques and inspire new research directions for WSR in 6G networks.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"28 ","pages":"3521-3563"},"PeriodicalIF":34.4,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143939866","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}
With the widespread application of digital twin (DT) technology in network optimization and intelligent management, its integration with large language models (LLMs) presents immense potential. LLMs excel in natural language processing, multimodal analysis, and real-time optimization, enabling innovative solutions for intelligent monitoring, resource allocation, and decision-making in complex network environments. This paper systematically reviews the development of DTs and LLMs, elaborates on their core principles and application scenarios, and examines the capabilities of LLM-driven DTs in key network optimization tasks, including traffic prediction, fault diagnosis, resource allocation, and multi-objective optimization. By leveraging real-time data from DTs, LLMs can dynamically generate optimization strategies, enabling precise monitoring and intelligent tuning. Furthermore, this paper explores the potential of integrating LLMs and DTs to address complex challenges such as data quality, latency sensitivity, and energy consumption demands, while summarizing existing technical bottlenecks. Finally, the paper proposes several potential research directions to address these challenges, offering a comprehensive perspective for advancing the efficiency and automation of next-generation intelligent networks.
{"title":"A Survey on Applications of Large Language Model-Driven Digital Twins for Intelligent Network Optimization","authors":"Zhiqi Guo;Fengxiao Tang;Linfeng Luo;Ming Zhao;Nei Kato","doi":"10.1109/COMST.2025.3568637","DOIUrl":"10.1109/COMST.2025.3568637","url":null,"abstract":"With the widespread application of digital twin (DT) technology in network optimization and intelligent management, its integration with large language models (LLMs) presents immense potential. LLMs excel in natural language processing, multimodal analysis, and real-time optimization, enabling innovative solutions for intelligent monitoring, resource allocation, and decision-making in complex network environments. This paper systematically reviews the development of DTs and LLMs, elaborates on their core principles and application scenarios, and examines the capabilities of LLM-driven DTs in key network optimization tasks, including traffic prediction, fault diagnosis, resource allocation, and multi-objective optimization. By leveraging real-time data from DTs, LLMs can dynamically generate optimization strategies, enabling precise monitoring and intelligent tuning. Furthermore, this paper explores the potential of integrating LLMs and DTs to address complex challenges such as data quality, latency sensitivity, and energy consumption demands, while summarizing existing technical bottlenecks. Finally, the paper proposes several potential research directions to address these challenges, offering a comprehensive perspective for advancing the efficiency and automation of next-generation intelligent networks.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"28 ","pages":"3388-3411"},"PeriodicalIF":34.4,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143930621","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 : 2025-03-07DOI: 10.1109/COMST.2025.3567765
Georg K. J. Fischer;Thomas Schaechtle;Andrea Gabbrielli;Joan Bordoy;Ivo Häring;Fabian Höflinger;Stefan J. Rupitsch
Angle-of-Arrival (AoA), as well as Angle-of-Departure (AoD) localization are general principles for performing localization based on angular measurements. In recent years, these principles have been gaining interest over more traditional techniques in the field of indoor localization and positioning. In contrast to Time-of-Arrival (ToA) and Time Difference of Arrival (TDoA)-based localization, AoA may do so without requiring a high number of anchor nodes or effective synchronization between them, with the trade-off of higher hardware and algorithmic complexity. Research on angular-based localization encompasses a wide range of technologies, each with its own advantages and disadvantages for dealing with the generally more complex propagation channels of indoor environments, as opposed to those in outdoor settings. In this contribution, we perform a systematic survey and meta analysis of the field of angular-based indoor localization systems, covering the technologies: Acoustic Positioning, Wi-Fi, Bluetooth, Ultra-Wideband (UWB), Light-based Positioning, Positioning in Cellular Networks (like 5G), mmWave, Terahertz-band Localization, Radio Frequency Identification (RFID), and RADAR. The research and literature on algorithms are examined as well. Furthermore, a new set of design considerations for angular-based localization systems is proposed, as well as several trade-offs between technologies, are discussed, and future research directions presented. Since angular-based localization is expected to play a key role in the future of indoor localization, this contribution provides a structure for researchers, as well as practitioners, to find a unified perspective on the topic.
{"title":"A Systematic Survey and Comparative Analysis of Angular-Based Indoor Localization and Positioning Technologies","authors":"Georg K. J. Fischer;Thomas Schaechtle;Andrea Gabbrielli;Joan Bordoy;Ivo Häring;Fabian Höflinger;Stefan J. Rupitsch","doi":"10.1109/COMST.2025.3567765","DOIUrl":"10.1109/COMST.2025.3567765","url":null,"abstract":"Angle-of-Arrival (AoA), as well as Angle-of-Departure (AoD) localization are general principles for performing localization based on angular measurements. In recent years, these principles have been gaining interest over more traditional techniques in the field of indoor localization and positioning. In contrast to Time-of-Arrival (ToA) and Time Difference of Arrival (TDoA)-based localization, AoA may do so without requiring a high number of anchor nodes or effective synchronization between them, with the trade-off of higher hardware and algorithmic complexity. Research on angular-based localization encompasses a wide range of technologies, each with its own advantages and disadvantages for dealing with the generally more complex propagation channels of indoor environments, as opposed to those in outdoor settings. In this contribution, we perform a systematic survey and meta analysis of the field of angular-based indoor localization systems, covering the technologies: Acoustic Positioning, Wi-Fi, Bluetooth, Ultra-Wideband (UWB), Light-based Positioning, Positioning in Cellular Networks (like 5G), mmWave, Terahertz-band Localization, Radio Frequency Identification (RFID), and RADAR. The research and literature on algorithms are examined as well. Furthermore, a new set of design considerations for angular-based localization systems is proposed, as well as several trade-offs between technologies, are discussed, and future research directions presented. Since angular-based localization is expected to play a key role in the future of indoor localization, this contribution provides a structure for researchers, as well as practitioners, to find a unified perspective on the topic.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"28 ","pages":"3830-3869"},"PeriodicalIF":34.4,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10990274","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143920244","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}
The evolution of 6G networks necessitates robust authentication and key agreement (AKA) protocols to counter emerging security challenges, particularly the threat posed by quantum computing. Existing 5G-AKA protocols remain vulnerable to user tracking, replay attacks, and false base station impersonation, while Elliptic Curve Cryptography (ECC) and RSA-based key exchanges face imminent obsolescence due to quantum attacks. This study examines the vulnerabilities of 5G-AKA and explores hybrid post-quantum cryptography (PQC) as a transitional security solution for 6G networks. We evaluate NIST-standardized PQC algorithms, focusing on their computational overhead, key size efficiency, and adaptability to heterogeneous network environments, including IoT and ultra-low latency applications. A comparative analysis of hybrid cryptographic schemes demonstrates that lattice-based (Kyber, Dilithium), hash-based (SPHINCS+), and code-based (BIKE, Classic McEliece) PQC techniques provide varying trade-offs between security, efficiency, and deployment feasibility. Furthermore, we propose a quantum-resistant 6G-AKA framework, integrating hybrid PQC, AI-driven trust mechanisms, and decentralized authentication to ensure scalability and interoperability. Experimental benchmarks highlight potential performance constraints, including latency in PQC-based key exchange and resource limitations in edge computing. Addressing these challenges requires the optimization of lightweight PQC implementations, formal security validation, and global standardization efforts. Our findings provide a roadmap for the secure transition to 6G authentication protocols, ensuring resilience against both classical and quantum threats.
{"title":"Toward 6G Authentication and Key Agreement Protocol: A Survey on Hybrid Post Quantum Cryptography","authors":"Togu Novriansyah Turnip;Birger Andersen;César Vargas-Rosales","doi":"10.1109/COMST.2025.3567439","DOIUrl":"10.1109/COMST.2025.3567439","url":null,"abstract":"The evolution of 6G networks necessitates robust authentication and key agreement (AKA) protocols to counter emerging security challenges, particularly the threat posed by quantum computing. Existing 5G-AKA protocols remain vulnerable to user tracking, replay attacks, and false base station impersonation, while Elliptic Curve Cryptography (ECC) and RSA-based key exchanges face imminent obsolescence due to quantum attacks. This study examines the vulnerabilities of 5G-AKA and explores hybrid post-quantum cryptography (PQC) as a transitional security solution for 6G networks. We evaluate NIST-standardized PQC algorithms, focusing on their computational overhead, key size efficiency, and adaptability to heterogeneous network environments, including IoT and ultra-low latency applications. A comparative analysis of hybrid cryptographic schemes demonstrates that lattice-based (Kyber, Dilithium), hash-based (SPHINCS+), and code-based (BIKE, Classic McEliece) PQC techniques provide varying trade-offs between security, efficiency, and deployment feasibility. Furthermore, we propose a quantum-resistant 6G-AKA framework, integrating hybrid PQC, AI-driven trust mechanisms, and decentralized authentication to ensure scalability and interoperability. Experimental benchmarks highlight potential performance constraints, including latency in PQC-based key exchange and resource limitations in edge computing. Addressing these challenges requires the optimization of lightweight PQC implementations, formal security validation, and global standardization efforts. Our findings provide a roadmap for the secure transition to 6G authentication protocols, ensuring resilience against both classical and quantum threats.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"28 ","pages":"3311-3345"},"PeriodicalIF":34.4,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143915531","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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