IEEE Communications Surveys and Tutorials最新文献

{"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":"Generative AI Meets 6G and Beyond: Diffusion Models for Semantic Communications","authors":"Hai-Long Qin;Jincheng Dai;Guo Lu;Shuo Shao;Sixian Wang;Tongda Xu;Wenjun Zhang;Ping Zhang;Khaled B. Letaief","doi":"10.1109/COMST.2026.3690542","DOIUrl":"https://doi.org/10.1109/COMST.2026.3690542","url":null,"abstract":"Semantic communications mark a paradigm shift from bit-accurate transmission toward meaning-centric communication, essential as wireless systems approach theoretical capacity limits. The emergence of generative AI has catalyzed generative semantic communications, where receivers reconstruct content from minimal semantic cues by leveraging learned priors. Among generative approaches, diffusion models stand out for their superior generation quality, stable training dynamics, and rigorous theoretical foundations. However, the field currently lacks systematic guidance connecting diffusion techniques to communication system design, forcing researchers to navigate disparate literatures. This article provides the first comprehensive tutorial on diffusion models for generative semantic communications. We present score-based diffusion foundations and systematically review three technical pillars: conditional diffusion for controllable generation, efficient diffusion for accelerated inference, and generalized diffusion for cross-domain adaptation. In addition, we introduce an inverse problem perspective that reformulates semantic decoding as posterior inference, bridging semantic communications with computational imaging. Through analysis of human-centric, machine-centric, and agent-centric scenarios, we illustrate how diffusion models enable extreme compression while maintaining semantic fidelity and robustness. By bridging generative AI innovations with communication system design, this article aims to establish diffusion models as foundational components of next-generation wireless networks and beyond.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"28 ","pages":"6241-6281"},"PeriodicalIF":34.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147937389","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":"Lightweight Authentication Protocols for Secure IoT Communication Networks: A Comprehensive Survey, Taxonomy, and Open Challenges","authors":"Baraq Ghaleb;Jawad Ahmad;Ahmed Al-Dubai;Muhammad Khurram Khan;Shahid Latif;Muhammad Shahbaz Khan","doi":"10.1109/COMST.2026.3691266","DOIUrl":"https://doi.org/10.1109/COMST.2026.3691266","url":null,"abstract":"The exponential growth of the Internet of Things (IoT) demands robust yet efficient authentication mechanisms to secure heterogeneous communication networks including resource-constrained devices and multi-tier infrastructures. This paper presents a systematic and comprehensive survey of lightweight authentication protocols in IoT communication networks, supported by a structured systematic literature review methodology. The survey outlines foundational cryptographic primitives and security requirements, and introduces a multi-dimensional taxonomy that maps authentication schemes across cryptographic primitives, authentication types, application domains, security goals, and implementation environments. Building on this taxonomy, the paper reviews cryptography-based, hardware-based, and hybrid authentication approaches, followed by quantitative comparative analysis of computational cost, communication and storage overhead, energy consumption, and formal security validation models. The results show that hash/XOR-based schemes offer very low computation but remain vulnerable to advanced attacks, PUF-based designs provide hardware-rooted trust yet suffer from environmental instability and reconstruction overhead, ECC-based schemes achieve strong security with compact keys but incur non-trivial resource cost, while post-quantum mechanisms enhance quantum resilience but currently impose significant communication and latency burdens for constrained IoT devices. Blockchain-assisted authentication improves decentralised trust at the expense of protocol and infrastructure overhead. Finally, the paper consolidates critical insights and open challenges including scalable key management, lightweight formal security assurance, reliable hardware trust, and post-quantum readiness, providing directions for future secure IoT authentication research.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"28 ","pages":"6282-6317"},"PeriodicalIF":34.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148003533","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":"Toward Secure Reflection: A Survey on Physical Layer Security in Backscatter Communications","authors":"Niya Luo;Yishan Yang;Zheng Yan;Yifan Zhang","doi":"10.1109/COMST.2026.3706426","DOIUrl":"10.1109/COMST.2026.3706426","url":null,"abstract":"Backscatter communication (BC) has emerged as a promising technology for low-cost and ultra-low-power wireless applications. However, the inherent openness of wireless channels, the passive reflection characteristics of BC systems, and stringent resource constraints introduce significant security vulnerabilities. Conventional cryptographic solutions are often impractical due to their high computational complexity, while physical layer security (PLS) offers lightweight and cost-effective security guarantees. Despite the growing interest, a comprehensive survey on PLS techniques for BC systems remains lacking. This paper presents the first comprehensive survey on PLS techniques for BC systems, encompassing Physical Layer Authentication (PLA), Physical Layer Key Generation (PLKG), Physical Layer Secure Transmission (PLST), and Physical Layer Anti-Jamming Transmission (PLAJT), along with the integration of emerging technologies such as Reconfigurable Intelligent Surfaces (RIS) and autonomous aerial vehicles (AAVs). Structured around the unique constraints and security implications of BC systems, this survey contributes three distinctive perspectives: a BC-specific threat model grounded in intrinsic security characteristics, a practical evaluation framework, and a cross-paradigm analysis revealing complementarities and performance differences of different PLS paradigms. Specifically, this paper first introduces the fundamental principles of BC systems. It identifies the impact of system characteristics on security performance and summarizes existing potential security threats. It also elaborates on the core principles and basic concepts of PLS, RIS and AAV technologies. This paper further establishes a classification framework of PLS systems suitable for BC scenarios and constructs a complete evaluation criterion system to support systematic qualitative and quantitative analysis of existing research works. With the established classification framework and evaluation criterion system, this paper conducts a systematic review on state of the art PLS solutions for BC systems published in recent years. This review clarifies the mainstream prerequisite assumptions and essential performance trade-offs widely adopted in the design of PLS for BC systems. This paper also outlines the design principles of PLS for BC systems. It provides system designers with a comprehensive analytical perspective to further promote research on BC system oriented PLS technologies. This paper finally summarizes a set of important open challenges and presents targeted future research directions.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"28 ","pages":"6447-6480"},"PeriodicalIF":50.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148314205","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":"Artificial Intelligence for Satellite Communication: A Survey","authors":"Gianluca Fontanesi;Flor Ortíz;Eva Lagunas;Luis Manuel Garcés-Socarrás;Victor Monzon Baeza;Miguel Ángel Vázquez;Juan Andrés Vásquez-Peralvo;Mario Minardi;Ha Nguyen Vu;Puneeth Jubba Honnaiah;Clement Lacoste;Youssouf Drif;Liz Martinez Marrero;Saed Daoud;Tedros Salih Abdu;Geoffrey Eappen;Junaid Ur Rehman;Wallace Alves Martins;Pol Henarejos;Hayder Al-Hraishawi;Juan Carlos Merlano Duncan;Thang X. Vu;Symeon Chatzinotas","doi":"10.1109/COMST.2025.3534617","DOIUrl":"10.1109/COMST.2025.3534617","url":null,"abstract":"This paper provides a comprehensive survey on the application and development of Artificial Intelligence (AI) and Machine Learning (ML) in satellite communication (SATCOM). It explores the increasing integration of AI/ML technologies in SATCOM systems, highlighting their potential to enhance performance, efficiency, and adaptability in response to growing demands for connectivity and data processing. The survey categorizes various use cases across different layers of satellite networks, detailing conventional solutions and the advantages of employing AI/ML techniques. It discusses the challenges associated with onboard processing, including hardware constraints, radiation tolerance, and the need for efficient resource management. Furthermore, the document examines the role of neuromorphic computing and COTS (Commercial Off-The-Shelf) devices in facilitating AI applications in space environments. Finally, we discuss the long-term developments of AI in the SATCOM sector and potential research directions. Overall, the survey emphasizes the transformative impact of AI/ML on the future of SATCOM, paving the way for innovative solutions in next-generation satellite networks.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"28 ","pages":"1381-1435"},"PeriodicalIF":50.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143417532","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":"Survey on Near-Space Information Networks: Channel Modeling, Transmission, and Networking Perspectives","authors":"Xianbin Cao;Xiaoning Su;Peng Yang;Yue Gao;Dapeng Oliver Wu;Tony Q. S. Quek","doi":"10.1109/COMST.2025.3549523","DOIUrl":"10.1109/COMST.2025.3549523","url":null,"abstract":"Near-space information networks (NSINs) composed of high-altitude platforms (HAPs) and high- and low-altitude autonomous aerial vehicles (AAVs) are a new regime for providing quick, robust, and cost-efficient sensing and communication services. Precipitated by innovations and breakthroughs in manufacturing, materials, communications, electronics, and control techniques, NSINs have been envisioned as an essential component of the emerging sixth-generation of mobile communication systems. This article reveals some critical issues needing to be tackled in NSINs through conducting experiments and discusses the latest advances in NSINs in the research areas of channel modeling, transmission, and networking from a forward-looking, comparative, and technical evolutionary perspective. In this article, we highlight the characteristics of NSINs and present the promising use cases of NSINs. The impact of airborne platforms’ unstable movements on the phase delays of onboard antenna arrays with diverse structures is mathematically analyzed. The recent advances in HAP and AAV channel modeling are elaborated on, along with the significant differences between HAP and AAV channel modeling. The promising techniques and communication protocols of the physical (PHY) layer, medium access control (MAC) layer, network layer, and transport layer of NSINs for achieving efficient transmission over NSINs are reviewed. A comprehensive review of the networking techniques of NSINs in network deployment, handoff management, and network management aspects is provided. Besides, experiments have been conducted using practical NSINs to verify the performance of some techniques. Finally, we outline some open issues and promising directions for NSINs deserved for future study and discuss the corresponding challenges.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"28 ","pages":"672-715"},"PeriodicalIF":50.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143599542","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":"A Survey on Magnetic Sensing and Communication: Technologies, Sensors, and Applications","authors":"Yufei Ma;Xiuzhen Guo;Jianpeng Li;Wenxuan Wang;Yongming Chen;Jiabao Pan;Jiming Chen","doi":"10.1109/COMST.2025.3578396","DOIUrl":"10.1109/COMST.2025.3578396","url":null,"abstract":"Magnetic sensing and communication technologies have undergone rapid advancements, playing a critical role in modern applications. From consumer electronics to industrial systems, magnetic sensors, such as Hall effect (HALL) sensors, Giant Magnetoresistance (GMR) sensors, Anisotropic Magnetoresistance (AMR) sensors, and Tunnel Magnetoresistance (TMR) sensors, have emerged as essential components due to their contactless operation, durability, and resistance to environmental factors. This survey provides a comprehensive review of technologies, sensors, and applications of magnetic sensing and communication. In this survey, we first introduce the sensing principle and hardware platform of these four different types of magnetic sensors. We then provide a comprehensive review of existing magnetic sensing and communication works. We further explore magnetic sensing and communication tasks and their application in fields including automotive systems, smart grid management, medical equipment, and security systems. We also discuss current research challenges and potential directions for future development in magnetic technologies.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"28 ","pages":"1776-1802"},"PeriodicalIF":50.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144259968","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":"Integrated Sensing and Edge AI: Realizing Intelligent Perception in 6G","authors":"Zhiyan Liu;Xu Chen;Hai Wu;Zhanwei Wang;Xianhao Chen;Dusit Niyato;Kaibin Huang","doi":"10.1109/COMST.2025.3592989","DOIUrl":"10.1109/COMST.2025.3592989","url":null,"abstract":"Sensing and edge artificial intelligence (AI) are envisioned as two essential and interconnected functions in sixth-generation (6G) mobile networks. On the one hand, sensing-empowered applications rely on powerful AI models to extract features and understand semantics from ubiquitous wireless sensors. On the other hand, the massive amount of sensory data serves as the fuel to continuously refine edge AI models. This deep integration of sensing and edge AI has given rise to a new task-oriented paradigm known as integrated sensing and edge AI (ISEA), which features a holistic design approach to communication, AI computation, and sensing for optimal sensing-task performance. In this article, we present a comprehensive survey for ISEA. We first provide technical preliminaries for sensing, edge AI, and new communication paradigms in ISEA. Then, we study several use cases of ISEA to demonstrate its practical relevance and introduce current standardization and industrial progress. Next, the design principles, metrics, tradeoffs, and architectures of ISEA are established, followed by a thorough overview of ISEA techniques, including digital air interface, over-the-air computation, and advanced signal processing. Its interplay with various 6G advancements, e.g., new physical-layer and networking techniques, are presented. Finally, we present future research opportunities in ISEA, including the integration of foundation models, convergence of ISEA and integrated sensing and communications (ISAC), ultra-low-latency ISEA, and practicality issues.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"28 ","pages":"2725-2770"},"PeriodicalIF":50.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144736946","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":"A Comprehensive Survey on Software-Defined Wide Area Network","authors":"Sebastian Troia;Luca Borgianni;Giacomo Sguotti;Stefano Giordano;Guido Maier","doi":"10.1109/COMST.2025.3594678","DOIUrl":"10.1109/COMST.2025.3594678","url":null,"abstract":"The rise of Software-defined wide area network (SD-WAN) a decade ago has ushered in a new era of networking opportunities for organizations worldwide. As enterprises undergo digital transformation fueled by cloud computing adoption and the imperative for enhanced connectivity, SD-WAN has emerged as a transformative paradigm. This survey paper unpacks the intricate ecosystem of SD-WAN technology, offering a deep dive into its foundational principles, architectural components, and diverse deployment scenarios. We explore modern SD-WAN architectures, analyzing key elements such as customer premises equipment (CPE), underlay and overlay networks, controllers, and orchestration planes. By shedding light on the mechanisms that drive SD-WAN’s agility and efficiency, we provide critical insights into its transformative potential. Beyond architecture, we examine essential operational aspects, including traffic engineering, performance monitoring, and network resources management within the SD-WAN framework. We also identify key challenges and research gaps, charting a path for future advancements in the field. This comprehensive study serves as a valuable resource for academics, researchers, and industry professionals navigating the evolving landscape of enterprise networking in the era of cloud-driven digital transformation.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"28 ","pages":"2805-2845"},"PeriodicalIF":50.6,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144763323","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}