IEEE Communications Surveys and Tutorials最新文献

{"title":"A Survey on Artificial Intelligence Techniques for Improved Rich Media Content Delivery in a 5G and Beyond Network Slicing Context","authors":"Fazal E. Subhan;Abid Yaqoob;Cristina Hava Muntean;Gabriel-Miro Muntean","doi":"10.1109/COMST.2024.3442149","DOIUrl":"10.1109/COMST.2024.3442149","url":null,"abstract":"Network slicing is an emerging paradigm driven by an objective to provide support for personalized services in the highly evolving and dynamic 5G and beyond network environment. The management of network functions and resources under network slicing architecture for rich media content delivery is a challenging task that requires an efficient decision at all network levels to maintain the required Quality of Service (QoS) and Quality of Experience (QoE). Integrating Artificial Intelligence (AI) in the network slice architecture for taking efficient network decision is one of the potential solutions to the problem. In this paper, we summarize the network slicing enabling technologies such as Software Defined Network (SDN), Network Function Virtualization (NFV), Multi-access Edge Computing (MEC) in the context of AI for improving the rich media content delivery. In addition, we present a comprehensive survey on content-centric networking and delivery solutions based on network slicing technologies i.e., MPEG-DASH-enabled Information Centric Networking (ICN) and Content Delivery Network (CDN) for intelligent rich media content caching and prefetching, predictive analysis, content preference optimization, secure resource allocation, and dynamic traffic steering. Several standardization and orchestration mechanisms of 5G network slicing proposed by 3GPP are then presented. Finally, the challenges of AI-enabled 5G network slicing for immersive content delivery are outlined with potential solutions and future research opportunities.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 2","pages":"1427-1487"},"PeriodicalIF":34.4,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10636754","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141986578","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":"A Survey on Haptics: Communication, Sensing and Feedback","authors":"Melika Emami;Amirhossein Bayat;Rahim Tafazolli;Atta Quddus","doi":"10.1109/COMST.2024.3444051","DOIUrl":"10.1109/COMST.2024.3444051","url":null,"abstract":"Haptic communications represent a vast area of research focused on integrating the sense of touch into digital sensory experiences. Achieving effective haptic communication requires meticulous design and implementation of all subsystems. As implied by the term, the two primary subsystems are haptic and communication. Haptic refers to replicating the touch sensation in various applications such as augmented reality, virtual reality and teleoperation, and communication involves optimising network structures to transmit and receive haptic information alongside other sensory data. In this survey paper, we discuss both haptic interfaces and network requirements simultaneously. For haptic interfaces, we comprehensively explore the mechanisms of touch perception, haptic sensing, and haptic feedback. We delve into haptic sensing by examining state-of-the-art sensors and approaches to capture data related to touch, such as pressure, force, and motion, and translate these physical interactions into digital data that a haptic system can interpret and respond to. Subsequently, we discuss various methods of achieving haptic feedback, including different mechanical actuators and electrical stimulation. We also investigate the incorporation of artificial intelligence in this field, proposing new areas where it could enhance system performance. Additionally, we address open challenges and future research directions, covering critical issues related to privacy, data transmission, cybersickness, performance and wearability of haptic interface, integrated systems, power supply and evaluation of these devices. Through this interdisciplinary approach, which merges haptic feedback, haptic sensing, and communication, our paper aims to inspire further research and development, ultimately advancing technology and enhancing haptic experiences.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 3","pages":"2006-2050"},"PeriodicalIF":34.4,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10637258","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141986333","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":"Modeling, Estimation, and Applications of Phase Noise in Wireless Communications: A Survey","authors":"Zikai Chang;Yuntao Xu;Junjie Chen;Ning Xie;Yejun He;Hongbin Li","doi":"10.1109/COMST.2024.3443158","DOIUrl":"10.1109/COMST.2024.3443158","url":null,"abstract":"Phase noise is inevitably present in wireless communications, arising from both hardware impairments and imperfect channel estimation, and has substantial implications on the integrity and efficiency of communication systems. However, phase noise brings more to wireless systems than just negative effects. For instance, phase noise can be used as a physical layer feature to authenticate received signals and as a source for random number generation. There is a surprising lack of a comprehensive overview of the state-of-the-art estimation methods and applications of phase noise in wireless communications. In this paper, we conduct the first comprehensive survey on the modeling, estimation, and applications of phase noise in wireless communications. We review the state-of-the-art phase-noise models, phase-noise estimation, and mitigation techniques via joint transmit-receive design, as well as applications of phase noise in wireless communications, while highlighting contributions and critical issues of each reviewed work. Finally, we provide an expansive set of research directions, accompanying challenges, and potential solutions related to phase noise that could shape the future of phase noise research in wireless communications.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 2","pages":"912-940"},"PeriodicalIF":34.4,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141980812","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":"Intellicise Wireless Networks From Semantic Communications: A Survey, Research Issues, and Challenges","authors":"Ping Zhang;Wenjun Xu;Yiming Liu;Xiaoqi Qin;Kai Niu;Shuguang Cui;Guangming Shi;Zhijin Qin;Xiaodong Xu;Fengyu Wang;Yue Meng;Chen Dong;Jincheng Dai;Qianqian Yang;Yaping Sun;Dahua Gao;Hui Gao;Shujun Han;Xiaodan Song","doi":"10.1109/COMST.2024.3443193","DOIUrl":"10.1109/COMST.2024.3443193","url":null,"abstract":"Information and communication technology (ICT) has been an essential part of modern society. However, the current communication systems are not sufficient to meet the demands of emerging applications. Intellicise (intelligent and concise) wireless networks, with their inherent characteristics of intelligence-endogenous and primitive-concise, have been proposed as a promising research direction. In this paper, we focus on intellicise wireless networks from semantic communication (SemCom). We present a comprehensive framework of intellicise wireless networks, including components such as brain for intellicise wireless networks (BIWN), intellicise signal processing, intellicise information transmission, intellicise network organization, and intellicise service bearing. We also investigate the enabling technologies and driving factors of intellicise wireless networks. Subsequently, we introduce the applications of intellicise wireless networks and envision new services. Finally, we outline the challenges of implementing intellicise wireless networks from a broad perspective and discuss possible solutions.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 3","pages":"2051-2084"},"PeriodicalIF":34.4,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141980527","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":"Phishing Webpage Detection: Unveiling the Threat Landscape and Investigating Detection Techniques","authors":"Aditya Kulkarni;Vivek Balachandran;Tamal Das","doi":"10.1109/COMST.2024.3441752","DOIUrl":"10.1109/COMST.2024.3441752","url":null,"abstract":"In the realm of cybersecurity, phishing stands as a prevalent cyber attack, where attackers employ various tactics to deceive users into gathering their sensitive information, potentially leading to identity theft or financial gain. Researchers have been actively working on advancing phishing webpage detection approaches to detect new phishing URLs, bolstering user protection. Nonetheless, the ever-evolving strategies employed by attackers, aimed at circumventing existing detection approaches and tools, present an ongoing challenge to the research community. This survey presents a systematic categorization of diverse phishing webpage detection approaches, encompassing URL-based, webpage content-based, third-party-based and visual techniques. Through a comprehensive review of these approaches and an in-depth analysis of existing literature, our study underscores current research gaps in phishing webpage detection. Furthermore, we suggest potential solutions to address some of these gaps, contributing valuable insights to the ongoing efforts to combat phishing attacks.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 2","pages":"974-1007"},"PeriodicalIF":34.4,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141974018","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-Based Cybersecurity for the Metaverse: Research Challenges and Opportunities","authors":"Abeer Awadallah;Khouloud Eledlebi;Mohamed Jamal Zemerly;Deepak Puthal;Ernesto Damiani;Kamal Taha;Tae-Yeon Kim;Paul D. Yoo;Kim-Kwang Raymond Choo;Man-Sung Yim;Chan Yeob Yeun","doi":"10.1109/COMST.2024.3442475","DOIUrl":"10.1109/COMST.2024.3442475","url":null,"abstract":"The metaverse, known as the next-generation 3D Internet, represents virtual environments that mirror the physical world. It is supported by innovative technologies such as digital twins and extended reality (XR), which elevate user experiences across various fields. However, the metaverse also introduces significant cybersecurity and privacy challenges that remain underexplored. Due to its complex multi-tech infrastructure, the metaverse requires sophisticated, automated, and intelligent cybersecurity measures to mitigate emerging threats effectively. Therefore, this paper is the first to explore Artificial Intelligence (AI)-driven cybersecurity techniques for the metaverse, examining academic and industrial perspectives. First, we provide an overview of the metaverse, presenting a detailed system model, diverse use cases, and insights into its current industrial status. We then present attack models and cybersecurity threats derived from the unique characteristics and technologies of the metaverse. Next, we review AI-driven cybersecurity solutions based on three critical aspects: User authentication, intrusion detection systems (IDS), and the security of digital assets, specifically for Blockchain and Non-fungible Tokens (NFTs). Finally, we highlight challenges and suggest future research opportunities to enhance metaverse security, privacy, and digital asset transactions.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 2","pages":"1008-1052"},"PeriodicalIF":34.4,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10634174","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141974056","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":"Navigating the Road Ahead: A Comprehensive Survey of Radio Resource Allocation for Vehicle Platooning in C-V2X Communications","authors":"Chenyu Yang;Chiew Foong Kwong;David Chieng;Pushpendu Kar;Kok-Lim Alvin Yau;Yusen Chen","doi":"10.1109/COMST.2024.3440033","DOIUrl":"10.1109/COMST.2024.3440033","url":null,"abstract":"Vehicle-to-everything (V2X) communications have emerged as an indispensable component of the Intelligent Transportation Systems (ITS), fostering innovations that enhance road safety and traffic efficiency. Within this transformative landscape, vehicle platooning has been identified by the Cellular-V2X (C-V2X) standards as an advanced V2X use case with the potential to reshape the future of ITS. However, the stringent requirements of such applications necessitate an optimized spectrum efficiency. Consequently, Radio Resource Allocation (RRA) has emerged as a critical and central component in addressing this challenge. This paper provides a comprehensive examination of RRA tailored specifically to the context of vehicle platooning. It presents an overview of fundamental concepts, including V2X communications, vehicle platooning, and RRA standards, which is followed by an in-depth review of the state-of-the-art, categorized based on the underlying communication technologies, RRA modes, and coverage conditions. By analyzing the existing literature, this paper identifies several key research challenges and potential opportunities, offering insightful guidance for shaping future research in this field.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 2","pages":"1326-1362"},"PeriodicalIF":34.4,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141904441","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 XAI for 5G and Beyond Security: Technical Aspects, Challenges and Research Directions","authors":"Thulitha Senevirathna;Vinh Hoa La;Samuel Marcha;Bartlomiej Siniarski;Madhusanka Liyanage;Shen Wang","doi":"10.1109/COMST.2024.3437248","DOIUrl":"10.1109/COMST.2024.3437248","url":null,"abstract":"With the advent of 5G commercialization, the need for more reliable, faster, and intelligent telecommunication systems is envisaged for the next generation beyond 5G (B5G) radio access technologies. Artificial Intelligence (AI) and Machine Learning (ML) are immensely popular in service layer applications and have been proposed as essential enablers in many aspects of 5G and beyond networks, from IoT devices and edge computing to cloud-based infrastructures. However, existing 5G ML-based security surveys tend to emphasize AI/ML model performance and accuracy more than the models’ accountability and trustworthiness. In contrast, this paper explores the potential of Explainable AI (XAI) methods, which would allow stakeholders in 5G and beyond to inspect intelligent black-box systems used to secure next-generation networks. The goal of using XAI in the security domain of 5G and beyond is to allow the decision-making processes of ML-based security systems to be transparent and comprehensible to 5G and beyond stakeholders, making the systems accountable for automated actions. In every facet of the forthcoming B5G era, including B5G technologies such as ORAN, zero-touch network management, and end-to-end slicing, this survey emphasizes the role of XAI in them that the general users would ultimately enjoy. Furthermore, we presented the lessons from recent efforts and future research directions on top of the currently conducted projects involving XAI.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 2","pages":"941-973"},"PeriodicalIF":34.4,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141880298","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":"Breaking the Interference and Fading Gridlock in Backscatter Communications: State-of-the-Art, Design Challenges, and Future Directions","authors":"Bowen Gu;Dong Li;Haiyang Ding;Gongpu Wang;Chintha Tellambura","doi":"10.1109/COMST.2024.3436082","DOIUrl":"10.1109/COMST.2024.3436082","url":null,"abstract":"As the Internet of Things (IoT) advances by leaps and bounds, a multitude of devices are becoming interconnected, marking the onset of an era where everything is connected. While this growth opens up opportunities for novel products and applications, it also leads to increased energy reliance on IoT devices, creating a significant bottleneck that hinders sustainable progress. Backscatter communication (BackCom), as a low-power and passive communication technology, emerges as one of the promising solutions to this energy impasse by reducing the manufacturing cost and energy consumption for IoT devices. However, BackCom systems also face some challenges, such as complex interference environments, including the direct-link interference (DLI) and the mutual interference (MI) between tags, which severely disrupt the efficiency of BackCom networks. Moreover, the double-path fading is another major issue that leads to a degraded system performance. To fully unleash the potential of BackComs, the purpose of this paper is to furnish a comprehensive review of existing solutions with a focus on addressing these challenges, offering an insightful analysis and comparison of various strategies. Specifically, we begin by introducing the preliminaries for BackCom, including its history, operating mechanisms, main architectures, etc., providing a foundational understanding of this field. Then, we delve into fundamental issues related to BackCom systems, such as solutions for the DLI, the MI, and the double-path fading. This paper thoroughly provides state-of-the-art advances for each case, particularly highlighting how the latest innovations in theoretical approaches and system design can strategically address these challenges. Finally, we explore emerging trends and challenges in BackComs by forecasting potential technological advancements and providing insights and guidelines for navigating the intricate landscape of future communication needs in a rapidly evolving IoT ecosystem.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 2","pages":"870-911"},"PeriodicalIF":34.4,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141862232","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":"Federated Learning for Urban Sensing Systems: A Comprehensive Survey on Attacks, Defences, Incentive Mechanisms, and Applications","authors":"Ayshika Kapoor;Dheeraj Kumar","doi":"10.1109/COMST.2024.3434510","DOIUrl":"10.1109/COMST.2024.3434510","url":null,"abstract":"In recent years, advancements in Artificial Intelligence (AI), the Internet of Things (IoT) and wireless technologies have propelled the evolution of smart cities. Urban sensing systems collect real-time data from urban areas for various applications, such as environmental monitoring, healthcare, and intelligent transportation, that contribute to the growth of smart cities. In urban sensing, the active participation of users gives rise to participatory sensing, where individuals contribute real-time data through their smartphones or IoT devices, but it encounters bottlenecks in communication, network latency, and user privacy with an exponential rise in data. A prominent characteristic of urban sensing applications is the highly individualized and personal nature of the data, e.g., location and time. Hence, adequate privacy and security provisions are required for these applications to succeed on a high scale. Conventional centralised machine learning approaches expose participants to potential vulnerabilities from malicious tasking servers or inference based on anonymized data. Federated learning (FL) has been proposed as the most viable alternative that leverages the advances in modern-day smartphones’ computation and communication capabilities by allowing participants to train local models on their devices. These models are aggregated by the application server to form a global model without the need for users to share their private data. However, large-scale FL-based urban sensing systems are still not practical due to various challenges associated with their real-life implementation. This paper presents a comprehensive survey addressing practical challenges in implementing FL-based urban sensing applications, e.g., inference attacks, poisoning attacks, and fair incentivization to participants while preserving privacy. We then provide an extensive survey on the use of FL in various urban sensing applications, highlighting that current applications do not simultaneously address all three aforementioned challenges. We conclude this survey by highlighting the research challenges to form a practical FL-based urban sensing system and future research directions.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"27 2","pages":"1293-1325"},"PeriodicalIF":34.4,"publicationDate":"2024-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141794710","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}