IEEE Communications Surveys and Tutorials最新文献

{"title":"Generalized Pinching-Antenna Systems: A Tutorial on Principles, Design Strategies, and Future Directions","authors":"Yanqing Xu;Jingjing Cui;Yongxu Zhu;Zhiguo Ding;Tsung-Hui Chang;Robert Schober;Vincent W. S. Wong;Octavia A. Dobre;George K. Karagiannidis;H. Vincent Poor;Xiaohu You","doi":"10.1109/COMST.2026.3674222","DOIUrl":"10.1109/COMST.2026.3674222","url":null,"abstract":"Pinching-antenna systems have emerged as a novel and transformative flexible-antenna architecture for next-generation wireless networks. They offer unprecedented flexibility and spatial reconfigurability by enabling dynamic positioning and activation of radiating elements along a signal-guiding medium (e.g., dielectric waveguide), which is not possible with conventional fixed antenna systems. In this paper, we introduce the concept of generalized pinching antenna systems, which retain the core principle of creating localized radiation points on demand, but can be physically realized with a variety of technologies. These include implementations based on dielectric waveguides, leaky coaxial cables, surface-wave guiding structures, and other types of media, employing different feeding methods and activation mechanisms (e.g., mechanical, electronic, or hybrid). Despite differences in their physical realizations, they all share the same inherent ability to form, reposition, or deactivate radiation sites as needed, enabling user-centric and dynamic coverage. We first describe the underlying physical mechanisms of representative generalized pinching-antenna realizations and their associated wireless channel models, highlighting their unique propagation and reconfigurability characteristics compared with conventional antennas. Then, using dielectric waveguide-based pinching antennas as primary examples, we review several representative pinching-antenna system architectures, ranging from single- to multiple-waveguide configurations, and discuss advanced design strategies tailored to these flexible deployments. Furthermore, we examine their integration with emerging wireless technologies to enable synergistic, user-centric solutions. Finally, we identify key open research challenges and outline future directions, charting a pathway toward the deployment of generalized pinching antennas in next-generation wireless networks.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"28 ","pages":"5872-5908"},"PeriodicalIF":34.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11434944","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147471240","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}

{"title":"Evaluating the Timeliness of Cryptography for Securing ICS Protocols in Smart Grid","authors":"Nethmi Hettiarachchi;Shabnam Saderi Oskouei;Arash Kariznovi;Kalikinkar Mandal","doi":"10.1109/COMST.2026.3680907","DOIUrl":"https://doi.org/10.1109/COMST.2026.3680907","url":null,"abstract":"For a safe and reliable power system, secure communication is crucial. Industrial control system (ICS) protocols, which play an important role in power grid communication, were designed decades ago without any built-in security techniques. Exploiting vulnerabilities in such protocols could result in unauthorized access, data manipulation and even lead to severe consequences such as complete blackouts of the power grid. Thus, the legacy ICS protocols utilized in smart grid communications should be transformed into secure protocols to mitigate cyberattacks. The fundamental building blocks to achieve security in the ICS protocols, covering confidentiality, integrity, authenticity, and non-repudiation lie in cryptography. This paper explores where the major cryptographic algorithms, such as stream ciphers, block ciphers, elliptic-curve cryptography schemes, hash functions and authenticated encryption stand when they are used to secure the ICS protocols, in terms of performance and cost, while balancing the inherent characteristics of the smart grid environments such as strict time and resource constraints. We extensively evaluate a range of contemporary cryptographic schemes and analyze their effectiveness in smart grid communication. We analyze the performance of these cryptographic primitives on both hardware (FPGA-based) and software (microcontroller-based) platforms, assessing their impact on system efficiency and security. This study will be invaluable for researchers in the smart grid domain in selecting cipher suites according to the development platform (hardware or software) to ensure the optimal balance between performance and security.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"28 ","pages":"5984-6017"},"PeriodicalIF":34.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147796076","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}

{"title":"Fluid Antennas: Pioneering a New Era in Next-Generation Wireless Communications","authors":"Dipen Bepari;Soumen Mondal;Anirban Bhowal;Keshav Singh;Hyundong Shin;Kai-Kit Wong;Derrick Wing Kwan Ng","doi":"10.1109/COMST.2026.3678505","DOIUrl":"10.1109/COMST.2026.3678505","url":null,"abstract":"The evolution towards sixth-generation (6G) wireless communication demands antenna technologies that are highly flexible, energy efficient, and scalable to satisfy the demands of massive connectivity, ultra-low latency, and dynamic propagation environments. Fluid antenna systems (FAS) have emerged as a promising solution, offering superior spatial reconfigurability through utilization of a single radio frequency (RF) chain. By dynamically adapting to channel conditions, FAS supports simplified hardware architectures, efficient interference suppression, and enhanced user separation, thereby eliminating the need for complex signal processing methods such as precoding or Successive Interference Cancellation (SIC). This survey presents a comprehensive review of FAS, starting with a tutorial-style introduction to its structural fundamentals, core multiple access mechanisms, and synergy with key 6G enablers including Non-Orthogonal Multiple Access (NOMA), Reconfigurable Intelligent Surfaces (RIS), Simultaneous Wireless Information and Power Transfer (SWIPT), Artificial Intelligence (AI) and Terahertz (THz) communication. In addition, it explores fluid material selection, port selection strategies, and recent advances in Channel State Information (CSI) acquisition, while providing a cross-layer perspective that links fluid material properties to communication performance. The transformative potential of FAS is further explored in the context of Multiple-Input Multiple-Output (MIMO) integration, AI-driven enhancements, and compatibility with other emerging wireless communication paradigms. The paper concludes by highlighting critical open challenges and proposing future research directions essential for fully realizing the capabilities of FAS in next-generation wireless systems.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"28 ","pages":"5596-5631"},"PeriodicalIF":34.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147524170","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}

{"title":"Hybrid GNN-Centric Architectures for AI-Native 6G Wireless Networks: A Comprehensive Survey","authors":"Mostafa Rahmani Ghourtani;Sajedeh Norouzi;Jinxuan Chen;Hamed Ahmadi;Torsten Braun;Kaushik Chowdhury;Alister Burr","doi":"10.1109/COMST.2026.3681198","DOIUrl":"https://doi.org/10.1109/COMST.2026.3681198","url":null,"abstract":"The growing complexity, scale, and heterogeneity of 6G wireless systems call for a shift toward AI-native architectures that are not only data-driven but also topology-aware, adaptive, and distributed. Graph Neural Networks (GNNs), with their native support for graph-structured data, are well-suited for modeling the irregular and dynamic relationships inherent in wireless communication systems. However, standalone GNNs may be insufficient to address key 6G challenges such as continual learning, data scarcity, and dynamic adaptation. This survey, therefore, explores the emerging synergy between GNNs and complementary AI paradigms, including deep reinforcement learning (DRL), federated learning (FL), meta-learning, generative models, mixture-of-experts (MoE), and world models, enabling hybrid AI–GNN architectures for intelligent control, predictive adaptation, and scalable optimization across the wireless stack. We systematically review how these GNN-centric AI models can support intelligent functionality in next-generation network architectures such as O-RAN, as well as core 6G domains, including edge computing for wireless systems, advanced MIMO, traffic prediction, and digital twins. The survey also highlights key challenges in hybrid AI–GNN adoption, particularly scalability, generalization across dynamic topologies, interpretability, and symbolic reasoning, and discusses emerging strategies such as graph causality learning, dynamic GNNs, and neurosymbolic integration to address them. By consolidating recent advances and outlining open research directions, this work positions hybrid AI–GNN architectures as a promising approach toward enabling intelligent, energy-efficient, and context-aware wireless systems for 6G and beyond.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"28 ","pages":"5678-5712"},"PeriodicalIF":34.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11474822","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147696668","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}

{"title":"Model Compression for Sustainable AI in xG Wireless Networks: Recent Advances, Challenges, and Future Directions","authors":"Fazal Muhammad Ali Khan;Mohammad Hallaq;Hatem Abou-Zeid;Omar Erak;Omer Waqar;Syed Ali Hassan;Omar Alhussein;Ekram Hossain","doi":"10.1109/COMST.2026.3682638","DOIUrl":"10.1109/COMST.2026.3682638","url":null,"abstract":"Next-generation (xG) wireless systems, including sixth-generation (6G) networks and beyond, are expected to deliver data rates on the order of terabits per second and sub-millisecond latency. Meeting these requirements increasingly relies on artificial intelligence (AI)-enabled radio access and physical-layer (PHY) processing. However, realizing such AI-driven PHY functionality with deep learning (DL) is challenging as deep neural networks (DNNs) are computationally intensive and memory hungry, often exceeding the capabilities of resource-constrained user equipment (UE) and edge hardware. This paper surveys model-compression techniques for efficient wireless intelligence, focusing on pruning, quantization, and knowledge distillation (KD), together with architectural and algorithmic optimizations. For each technique, we summarize theoretical foundations, practical implementation strategies, and wireless-specific considerations, and discuss how design choices translate into latency, energy, and memory outcomes on deployment hardware. We review applications across core PHY wireless tasks, including automatic modulation classification (AMC), channel state information (CSI) processing and feedback, beamforming (BF), recognition and identification, channel estimation and detection, and localization. Drawing on comparative analysis of more than 50 studies, we highlight trade-offs among model size, computational complexity, energy consumption, and task-level performance under wireless evaluation protocols. We further discuss hardware–software compatibility considerations for compressed model deployment and outline open challenges and future research directions for compression-aware deployment in xG wireless systems.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"28 ","pages":"5747-5791"},"PeriodicalIF":34.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147664112","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}

{"title":"Intrusion Detection and Prevention for Intra- and Inter-Vehicle Networks: A Comprehensive Survey","authors":"Aya El-Fatyany;Jabar Mahmood;Michael Abebe Berwo;Xiaohang Wang;Li Lu;Qiang Xue;Kui Ren","doi":"10.1109/COMST.2026.3674515","DOIUrl":"10.1109/COMST.2026.3674515","url":null,"abstract":"The security of intra- and inter-vehicle networks relies heavily on the implementation of intrusion detection systems (IDS) and intrusion prevention systems (IPS). These crucial technologies serve as the primary defence mechanisms against cyber threats, continuously monitoring and mitigating malicious activities within vehicles and across interconnected vehicular networks to ensure secure and reliable communication. This survey examines research works of IDS and IPS for intra- and inter-vehicle networks from 2020 to 2025, introducing an innovative taxonomy. This study analyzes various intrusion detection and prevention strategies, as well as attack surfaces, scenarios, and benchmark datasets for intra- and inter-vehicle networks. Furthermore, this paper emphasizes the necessity of collaborative IDS/IPS for both intra- and inter-vehicle networks and discuses directions for future research in this field.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"28 ","pages":"5345-5378"},"PeriodicalIF":34.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147471239","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}

{"title":"Large Language Models for Optimization in Next-Generation Wireless Network Management: A Survey","authors":"Bisheng Wei;Ruihong Jiang;Ruichen Zhang;Yinqiu Liu;Dusit Niyato;Yaohua Sun;Yang Lu;Yonghui Li;Shiwen Mao;Chau Yuen;Marco Di Renzo;Mugen Peng","doi":"10.1109/COMST.2026.3682137","DOIUrl":"10.1109/COMST.2026.3682137","url":null,"abstract":"The rapid advancement toward sixth-generation (6G) wireless networks has significantly intensified the complexity and scale of optimization problems, including resource allocation and trajectory design, often formulated as combinatorial problems in large discrete decision spaces. However, traditional optimization methods, such as heuristics and deep reinforcement learning (DRL), face practical challenges in meeting stringent latency and scalability requirements, especially in large-scale, highly dynamic, and reconfiguration-sensitive deployments in increasingly heterogeneous and resource-constrained network environments. Large language models (LLMs) present a transformative paradigm by enabling natural language-driven problem formulation, context-aware reasoning, and adaptive solution refinement through advanced semantic understanding and structured reasoning capabilities. This paper provides a systematic and comprehensive survey of LLM-enabled optimization frameworks tailored for wireless networks. We first introduce foundational design concepts and distinguish LLM-enabled methods from conventional optimization paradigms. Subsequently, we critically analyze key enabling methodologies, including natural language modeling, solver collaboration, and solution verification processes. Moreover, we explore representative case studies to demonstrate LLMs’ transformative potential in practical scenarios such as optimization formulation, low-altitude economy networking, and intent networking. Finally, we discuss current research challenges, examine prominent open-source frameworks and datasets, and identify promising future directions to facilitate robust, scalable, and trustworthy LLM-enabled optimization solutions for next-generation wireless networks.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"28 ","pages":"5713-5746"},"PeriodicalIF":34.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147664120","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}

{"title":"GNSS Jamming and Spoofing Threats in UAV Navigation: Countermeasure Status and Challenges","authors":"Yejia Zeng;Zukun Lu;Xiaoyu Zhao;Zhu Xiao;Shaojie Ni;Zhu Han;Keqin Li","doi":"10.1109/COMST.2026.3680438","DOIUrl":"10.1109/COMST.2026.3680438","url":null,"abstract":"Uncrewed aerial vehicles (UAVs) have become indispensable in both civilian and military applications. However, their reliance on Global Navigation Satellite System (GNSS)-based navigation exposes them to escalating threats from sophisticated jamming and spoofing attacks. These threats severely compromise operational safety and mission integrity, necessitating the development of effective countermeasures. This survey provides a comprehensive overview of GNSS interference threats specific to UAV navigation, with a focus on the analysis of jamming and spoofing attacks, and summarizes state-of-the-art techniques for interference detection and mitigation. We first review the principles of satellite navigation for UAVs and identify the inherent vulnerability of GNSS signals to interference. Then, we systematically examine existing countermeasures, including signal processing-based, array antenna-based, and artificial intelligence-based approaches, highlighting their effectiveness against jamming and spoofing. Despite these advances, significant challenges remain in ensuring robust UAV navigation in adversarial electromagnetic environments, particularly those arising from resource constraints, limited algorithmic flexibility, and the lack of UAV-specific countermeasures. To address these issues, we propose a hierarchical framework that integrates robust signal reception, intelligent algorithm optimization, and system-level collaboration. This framework provides practical strategies for enhancing the resilience of next-generation UAV navigation systems to complex interference.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"28 ","pages":"5909-5948"},"PeriodicalIF":34.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11474471","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147617621","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}

{"title":"Multibeam High Throughput Satellite: Hardware Foundation, Resource Allocation, and Precoding","authors":"Rui Chen;Wen-Xuan Long;Bingqian Wang;Yuan He;Ruijin Sun;Nan Cheng;Gan Zheng;Dusit Niyato","doi":"10.1109/COMST.2026.3673850","DOIUrl":"10.1109/COMST.2026.3673850","url":null,"abstract":"With its wide coverage and uninterrupted service, satellite communication is a critical technology for next-generation 6G communications. High throughput satellite (HTS) systems, utilizing multipoint beam and frequency multiplexing techniques, enable satellite communication capacity of up to Tbps to meet the growing traffic demand. Therefore, it is imperative to review the-state-of-the-art of multibeam HTS systems and identify their associated challenges and perspectives. Firstly, we summarize the multibeam HTS hardware foundations, including ground station systems, on-board payloads, and user terminals. Subsequently, we review the flexible on-board radio resource allocation approaches of bandwidth, power, time slot, and joint allocation schemes of HTS systems to optimize resource utilization and cater to non-uniform service demand. Additionally, we survey multibeam precoding methods for the HTS system to achieve full-frequency reuse and interference cancellation, which are classified according to different deployments such as single gateway precoding, multiple gateway precoding, on-board precoding, and hybrid on-board/on-ground precoding. Finally, we discuss the challenges related to Q/V band link outage, time and frequency synchronization of gateways, the accuracy of channel state information (CSI), payload light-weight development, and the application of deep learning (DL). Research on these topics will contribute to enhancing the performance of HTS systems and finally delivering high-speed data to areas underserved by terrestrial networks.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"28 ","pages":"5379-5415"},"PeriodicalIF":34.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147454470","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}

{"title":"“X of Information” Continuum: A Survey on AI-Driven Multi-Dimensional Metrics for Next-Generation Networked Systems","authors":"Beining Wu;Jun Huang;Shui Yu","doi":"10.1109/COMST.2026.3670279","DOIUrl":"10.1109/COMST.2026.3670279","url":null,"abstract":"The development of next-generation networking systems has shifted from throughput-based paradigms towards intelligent, information-aware designs that emphasize information quality, relevance, and utility rather than data volume. Classical network metrics such as latency and packet loss remain significant but are insufficient for modern intelligent applications that include autonomous vehicles, digital twins, and metaverse environments. This survey presents the first comprehensive study of the “X of Information” continuum through a systematic four-dimensional taxonomic framework that structures information metrics along temporal, quality/utility, reliability/robustness, and network/communication dimensions. We uncover increasing interdependencies among these dimensions, where temporal freshness triggers quality evaluation, which enables reliability appraisal that supports effective network delivery. Our analysis reveals that artificial intelligence technologies such as deep reinforcement learning, multi-agent systems, and neural optimization models enable adaptive, context-aware optimization of competing information quality objectives. Our study of six critical application domains that span autonomous transportation, industrial IoT, healthcare digital twins, UAV communications, LLM ecosystems, and metaverse settings illustrates the promise of multi-dimensional information metrics for diverse operational needs. The survey identifies key implementation challenges that include metric integration, information-driven resource allocation, semantic communication, and federated learning optimization. We highlight critical research agendas in unified theoretical models, AI-augmented dynamic optimization, and cross-layer orchestration mechanisms that lay the foundation for intelligent, value-aware communication systems.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"28 ","pages":"5307-5344"},"PeriodicalIF":34.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147361088","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}