Pub Date : 2023-04-03DOI: 10.1109/COMST.2023.3263921
Xinying Chen;Jianping An;Zehui Xiong;Chengwen Xing;Nan Zhao;F. Richard Yu;Arumugam Nallanathan
Information security has always been a critical issue in wireless networks. Apart from other secure techniques, covert communication emerges as a potential solution to security for wireless networks owing to its high-security level. In covert communication networks, the transmitter hides the transmitted signals into environmental or artificial noise by introducing randomness to avoid detection at the warden. By eliminating the existence of transmitted signals at the warden, information security can be preserved more solidly than other secure transmission techniques, i.e., without noticing the existence. Due to the promising security protection, covert communication has been successfully utilized in tremendous wireless communication scenarios. However, fundamental challenges in its practical implementation still exist, e.g., the effectiveness of randomness utilization, the low signal-to-interference-plus-noise ratio at legitimate users, etc. In this survey, we demonstrate a comprehensive review concentrating on the applications, solutions, and future challenges of covert communications. Specifically, the covert principle and research categories are first introduced. Then, the applications in the networks with different topologies and the effective covert techniques in the existing literature are reviewed. We also discuss the potential implementation of covert communications in future networks and the open challenges.
{"title":"Covert Communications: A Comprehensive Survey","authors":"Xinying Chen;Jianping An;Zehui Xiong;Chengwen Xing;Nan Zhao;F. Richard Yu;Arumugam Nallanathan","doi":"10.1109/COMST.2023.3263921","DOIUrl":"https://doi.org/10.1109/COMST.2023.3263921","url":null,"abstract":"Information security has always been a critical issue in wireless networks. Apart from other secure techniques, covert communication emerges as a potential solution to security for wireless networks owing to its high-security level. In covert communication networks, the transmitter hides the transmitted signals into environmental or artificial noise by introducing randomness to avoid detection at the warden. By eliminating the existence of transmitted signals at the warden, information security can be preserved more solidly than other secure transmission techniques, i.e., without noticing the existence. Due to the promising security protection, covert communication has been successfully utilized in tremendous wireless communication scenarios. However, fundamental challenges in its practical implementation still exist, e.g., the effectiveness of randomness utilization, the low signal-to-interference-plus-noise ratio at legitimate users, etc. In this survey, we demonstrate a comprehensive review concentrating on the applications, solutions, and future challenges of covert communications. Specifically, the covert principle and research categories are first introduced. Then, the applications in the networks with different topologies and the effective covert techniques in the existing literature are reviewed. We also discuss the potential implementation of covert communications in future networks and the open challenges.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"25 2","pages":"1173-1198"},"PeriodicalIF":35.6,"publicationDate":"2023-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49952910","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 : 2023-03-30DOI: 10.1109/COMST.2023.3263252
Jeroen van der Hooft;Hadi Amirpour;Maria Torres Vega;Yago Sanchez;Raimund Schatz;Thomas Schierl;Christian Timmerer
Video services are evolving from traditional two-dimensional video to virtual reality and holograms, which offer six degrees of freedom to users, enabling them to freely move around in a scene and change focus as desired. However, this increase in freedom translates into stringent requirements in terms of ultra-high bandwidth (in the order of Gigabits per second) and minimal latency (in the order of milliseconds). To realize such immersive services, the network transport, as well as the video representation and encoding, have to be fundamentally enhanced. The purpose of this tutorial article is to provide an elaborate introduction to the creation, streaming, and evaluation of immersive video. Moreover, it aims to provide lessons learned and to point at promising research paths to enable truly interactive immersive video applications toward holography.
{"title":"A Tutorial on Immersive Video Delivery: From Omnidirectional Video to Holography","authors":"Jeroen van der Hooft;Hadi Amirpour;Maria Torres Vega;Yago Sanchez;Raimund Schatz;Thomas Schierl;Christian Timmerer","doi":"10.1109/COMST.2023.3263252","DOIUrl":"https://doi.org/10.1109/COMST.2023.3263252","url":null,"abstract":"Video services are evolving from traditional two-dimensional video to virtual reality and holograms, which offer six degrees of freedom to users, enabling them to freely move around in a scene and change focus as desired. However, this increase in freedom translates into stringent requirements in terms of ultra-high bandwidth (in the order of Gigabits per second) and minimal latency (in the order of milliseconds). To realize such immersive services, the network transport, as well as the video representation and encoding, have to be fundamentally enhanced. The purpose of this tutorial article is to provide an elaborate introduction to the creation, streaming, and evaluation of immersive video. Moreover, it aims to provide lessons learned and to point at promising research paths to enable truly interactive immersive video applications toward holography.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"25 2","pages":"1336-1375"},"PeriodicalIF":35.6,"publicationDate":"2023-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49952790","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 : 2023-03-26DOI: 10.1109/COMST.2023.3280465
Nour Moustafa;Nickolaos Koroniotis;Marwa Keshk;Albert Y. Zomaya;Zahir Tari
The field of Explainable Artificial Intelligence (XAI) has garnered considerable research attention in recent years, aiming to provide interpretability and confidence to the inner workings of state-of-the-art deep learning models. However, XAI-enhanced cybersecurity measures in the Internet of Things (IoT) and its sub-domains, require further investigation to provide effective discovery of attack surfaces, their corresponding vectors, and interpretable justification of model outputs. Cyber defence involves operations conducted in the cybersecurity field supporting mission objectives to identify and prevent cyberattacks using various tools and techniques, including intrusion detection systems (IDS), threat intelligence and hunting, and intrusion prevention. In cyber defence, especially anomaly-based IDS, the emerging applications of deep learning models require the interpretation of the models’ architecture and the explanation of models’ prediction to examine how cyberattacks would occur. This paper presents a comprehensive review of XAI techniques for anomaly-based intrusion detection in IoT networks. Firstly, we review IDSs focusing on anomaly-based detection techniques in IoT and how XAI models can augment them to provide trust and confidence in their detections. Secondly, we review AI models, including machine learning (ML) and deep learning (DL), for anomaly detection applications and IoT ecosystems. Moreover, we discuss DL’s ability to effectively learn from large-scale IoT datasets, accomplishing high performances in discovering and interpreting security events. Thirdly, we demonstrate recent research on the intersection of XAI, anomaly-based IDS and IoT. Finally, we discuss the current challenges and solutions of XAI for security applications in the cyber defence perspective of IoT networks, revealing future research directions. By analysing our findings, new cybersecurity applications that require XAI models emerge, assisting decision-makers in understanding and explaining security events in compromised IoT networks.
{"title":"Explainable Intrusion Detection for Cyber Defences in the Internet of Things: Opportunities and Solutions","authors":"Nour Moustafa;Nickolaos Koroniotis;Marwa Keshk;Albert Y. Zomaya;Zahir Tari","doi":"10.1109/COMST.2023.3280465","DOIUrl":"https://doi.org/10.1109/COMST.2023.3280465","url":null,"abstract":"The field of Explainable Artificial Intelligence (XAI) has garnered considerable research attention in recent years, aiming to provide interpretability and confidence to the inner workings of state-of-the-art deep learning models. However, XAI-enhanced cybersecurity measures in the Internet of Things (IoT) and its sub-domains, require further investigation to provide effective discovery of attack surfaces, their corresponding vectors, and interpretable justification of model outputs. Cyber defence involves operations conducted in the cybersecurity field supporting mission objectives to identify and prevent cyberattacks using various tools and techniques, including intrusion detection systems (IDS), threat intelligence and hunting, and intrusion prevention. In cyber defence, especially anomaly-based IDS, the emerging applications of deep learning models require the interpretation of the models’ architecture and the explanation of models’ prediction to examine how cyberattacks would occur. This paper presents a comprehensive review of XAI techniques for anomaly-based intrusion detection in IoT networks. Firstly, we review IDSs focusing on anomaly-based detection techniques in IoT and how XAI models can augment them to provide trust and confidence in their detections. Secondly, we review AI models, including machine learning (ML) and deep learning (DL), for anomaly detection applications and IoT ecosystems. Moreover, we discuss DL’s ability to effectively learn from large-scale IoT datasets, accomplishing high performances in discovering and interpreting security events. Thirdly, we demonstrate recent research on the intersection of XAI, anomaly-based IDS and IoT. Finally, we discuss the current challenges and solutions of XAI for security applications in the cyber defence perspective of IoT networks, revealing future research directions. By analysing our findings, new cybersecurity applications that require XAI models emerge, assisting decision-makers in understanding and explaining security events in compromised IoT networks.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"25 3","pages":"1775-1807"},"PeriodicalIF":35.6,"publicationDate":"2023-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49963513","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}
Backscatter communication (BackCom) networks enable passive/battery-free Internet-of-Thing devices, providing reliable, massive connectivity while ensuring self-sustainability, low maintenance, and low costs. Effective channel codes and decoding algorithms are necessary to achieve these objectives. However, a comprehensive survey/review paper on such techniques for BackCom networks has not been available. This paper aims to fill this gap. Because tags have limited computational resources, traditional coding techniques may not suit them. We first describe the basics of BackCom, channel codes and their relevant design parameters, and codes for general communication networks. We address the BackCom limitations, requirements, and channel characteristics. As conventional codes may not seamlessly move to the BackCom arena, we identify the potential BackCom coding techniques and multiple access schemes. We further highlight potential approaches for addressing code implementation complexity and reliability. Finally, we discuss open issues, challenges, and potential future research directions.
{"title":"Coding Techniques for Backscatter Communications—A Contemporary Survey","authors":"Fatemeh Rezaei;Diluka Galappaththige;Chintha Tellambura;Sanjeewa Herath","doi":"10.1109/COMST.2023.3259224","DOIUrl":"https://doi.org/10.1109/COMST.2023.3259224","url":null,"abstract":"Backscatter communication (BackCom) networks enable passive/battery-free Internet-of-Thing devices, providing reliable, massive connectivity while ensuring self-sustainability, low maintenance, and low costs. Effective channel codes and decoding algorithms are necessary to achieve these objectives. However, a comprehensive survey/review paper on such techniques for BackCom networks has not been available. This paper aims to fill this gap. Because tags have limited computational resources, traditional coding techniques may not suit them. We first describe the basics of BackCom, channel codes and their relevant design parameters, and codes for general communication networks. We address the BackCom limitations, requirements, and channel characteristics. As conventional codes may not seamlessly move to the BackCom arena, we identify the potential BackCom coding techniques and multiple access schemes. We further highlight potential approaches for addressing code implementation complexity and reliability. Finally, we discuss open issues, challenges, and potential future research directions.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"25 2","pages":"1020-1058"},"PeriodicalIF":35.6,"publicationDate":"2023-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49952906","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 : 2023-03-22DOI: 10.1109/COMST.2022.3214905
Anas Chaaban;Zouheir Rezki;Mohamed-Slim Alouini
In the above article [1] , equations (116) and (122) appeared with errors. The correct equations and affected text follow.
在上述文章[1]中，方程（116）和（122）出现了错误。下面是正确的方程式和受影响的文本。
{"title":"Corrections to “On the Capacity of Intensity-Modulation Direct-Detection Gaussian Optical Wireless Communication Channels: A Tutorial”","authors":"Anas Chaaban;Zouheir Rezki;Mohamed-Slim Alouini","doi":"10.1109/COMST.2022.3214905","DOIUrl":"https://doi.org/10.1109/COMST.2022.3214905","url":null,"abstract":"In the above article \u0000<xref>[1]</xref>\u0000, \u0000<xref>equations (116)</xref>\u0000 and \u0000<xref>(122)</xref>\u0000 appeared with errors. The correct equations and affected text follow.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"25 2","pages":"1444-1444"},"PeriodicalIF":35.6,"publicationDate":"2023-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9739/10130694/10130701.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49952793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-22DOI: 10.1109/COMST.2023.3270753
Dusit Niyato
I welcome you to the second issue of the IEEE Communications Surveys and Tutorials in 2023. This issue includes 15 papers covering different aspects of communication networks. In particular, these articles survey and tutor various issues in “Wireless Communications,” “Cyber Security,” “Internet Technologies,” “Network and Service Management and Green Communications,” “Multimedia Communications,” “Network Virtualization” and “Optical Communications.” A brief account for each of these papers is given below.
{"title":"Editorial: Second Quarter 2023 IEEE Communications Surveys and Tutorials","authors":"Dusit Niyato","doi":"10.1109/COMST.2023.3270753","DOIUrl":"https://doi.org/10.1109/COMST.2023.3270753","url":null,"abstract":"I welcome you to the second issue of the IEEE Communications Surveys and Tutorials in 2023. This issue includes 15 papers covering different aspects of communication networks. In particular, these articles survey and tutor various issues in “Wireless Communications,” “Cyber Security,” “Internet Technologies,” “Network and Service Management and Green Communications,” “Multimedia Communications,” “Network Virtualization” and “Optical Communications.” A brief account for each of these papers is given below.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"25 2","pages":"i-v"},"PeriodicalIF":35.6,"publicationDate":"2023-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9739/10130694/10130703.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49953123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-19DOI: 10.1109/COMST.2023.3278239
Tao Jiang;Yu Zhang;Wenyuan Ma;Miaoran Peng;Yuxiang Peng;Mingjie Feng;Guanghua Liu
Battery-free Internet-of-Things (BF-IoT), which is realized by harvesting ambient energy to power the IoT devices, has emerged to reduce the energy consumption, and alleviate environmental concerns caused by extensive battery usage. However, current wireless technologies for IoT, such as Bluetooth, ZigBee, and long range radio (LoRa), cannot be efficiently supported by ambient energy due to high power requirement, making them unfit for BF-IoT applications. Backscatter communication (BackCom) is a promising enabling technology for BF-IoT as it achieves microwatt power consumption by eliminating the need of power-hungry radio components such as analog to digital converters. The integration of BF-IoT and BackCom is expected to revolutionize IoT applications and has attracted significant attention recently. However, several fundamental issues need to be addressed to fully harvest the potential of such integration. In this article, we conduct a comprehensive and in-depth survey of BackCom enabled BF-IoT (BackCom-BF-IoT), aiming to provide useful guidance for future research and application from a practical perspective. Specifically, we first introduce the basics of BackCom-BF-IoT by presenting its hardware architecture and key components. Then, we review the existing BackCom-BF-IoT prototypes, from which four fundamental issues related to BackCom are discussed, including link performance enhancement, multi-device concurrent transmission, security guarantee, and interplay between BackCom-BF-IoT system and ambient RF communication systems. For each fundamental issue, we thoroughly review state-of-the-art advances and discuss their prospects for practical BF-IoT applications. Finally, we provide an outlook of future research directions and several case studies.
{"title":"Backscatter Communication Meets Practical Battery-Free Internet of Things: A Survey and Outlook","authors":"Tao Jiang;Yu Zhang;Wenyuan Ma;Miaoran Peng;Yuxiang Peng;Mingjie Feng;Guanghua Liu","doi":"10.1109/COMST.2023.3278239","DOIUrl":"https://doi.org/10.1109/COMST.2023.3278239","url":null,"abstract":"Battery-free Internet-of-Things (BF-IoT), which is realized by harvesting ambient energy to power the IoT devices, has emerged to reduce the energy consumption, and alleviate environmental concerns caused by extensive battery usage. However, current wireless technologies for IoT, such as Bluetooth, ZigBee, and long range radio (LoRa), cannot be efficiently supported by ambient energy due to high power requirement, making them unfit for BF-IoT applications. Backscatter communication (BackCom) is a promising enabling technology for BF-IoT as it achieves microwatt power consumption by eliminating the need of power-hungry radio components such as analog to digital converters. The integration of BF-IoT and BackCom is expected to revolutionize IoT applications and has attracted significant attention recently. However, several fundamental issues need to be addressed to fully harvest the potential of such integration. In this article, we conduct a comprehensive and in-depth survey of BackCom enabled BF-IoT (BackCom-BF-IoT), aiming to provide useful guidance for future research and application from a practical perspective. Specifically, we first introduce the basics of BackCom-BF-IoT by presenting its hardware architecture and key components. Then, we review the existing BackCom-BF-IoT prototypes, from which four fundamental issues related to BackCom are discussed, including link performance enhancement, multi-device concurrent transmission, security guarantee, and interplay between BackCom-BF-IoT system and ambient RF communication systems. For each fundamental issue, we thoroughly review state-of-the-art advances and discuss their prospects for practical BF-IoT applications. Finally, we provide an outlook of future research directions and several case studies.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"25 3","pages":"2021-2051"},"PeriodicalIF":35.6,"publicationDate":"2023-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49963430","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 : 2023-03-13DOI: 10.1109/COMST.2023.3256323
Stephanie Baker;Wei Xiang
Healthcare systems are under increasing strain due to a myriad of factors, from a steadily ageing global population to the current COVID-19 pandemic. In a world where we have needed to be connected but apart, the need for enhanced remote and at-home healthcare has become clear. The Internet of Things (IoT) offers a promising solution. The IoT has created a highly connected world, with billions of devices collecting and communicating data from a range of applications, including healthcare. Due to these high volumes of data, a natural synergy with Artificial Intelligence (AI) has become apparent - big data both enables and requires AI to interpret, understand, and make decisions that provide optimal outcomes. In this extensive survey, we thoroughly explore this synergy through an examination of the field of the Artificial Intelligence of Things (AIoT) for healthcare. This work begins by briefly establishing a unified architecture of AIoT in a healthcare context, including sensors and devices, novel communication technologies, and cross-layer AI. We then examine recent research pertaining to each component of the AIoT architecture from several key perspectives, identifying promising technologies, challenges, and opportunities that are unique to healthcare. Several examples of real-world AIoT healthcare use cases are then presented to illustrate the potential of these technologies. Lastly, this work outlines promising directions for future research in AIoT for healthcare.
{"title":"Artificial Intelligence of Things for Smarter Healthcare: A Survey of Advancements, Challenges, and Opportunities","authors":"Stephanie Baker;Wei Xiang","doi":"10.1109/COMST.2023.3256323","DOIUrl":"https://doi.org/10.1109/COMST.2023.3256323","url":null,"abstract":"Healthcare systems are under increasing strain due to a myriad of factors, from a steadily ageing global population to the current COVID-19 pandemic. In a world where we have needed to be connected but apart, the need for enhanced remote and at-home healthcare has become clear. The Internet of Things (IoT) offers a promising solution. The IoT has created a highly connected world, with billions of devices collecting and communicating data from a range of applications, including healthcare. Due to these high volumes of data, a natural synergy with Artificial Intelligence (AI) has become apparent - big data both enables and requires AI to interpret, understand, and make decisions that provide optimal outcomes. In this extensive survey, we thoroughly explore this synergy through an examination of the field of the Artificial Intelligence of Things (AIoT) for healthcare. This work begins by briefly establishing a unified architecture of AIoT in a healthcare context, including sensors and devices, novel communication technologies, and cross-layer AI. We then examine recent research pertaining to each component of the AIoT architecture from several key perspectives, identifying promising technologies, challenges, and opportunities that are unique to healthcare. Several examples of real-world AIoT healthcare use cases are then presented to illustrate the potential of these technologies. Lastly, this work outlines promising directions for future research in AIoT for healthcare.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"25 2","pages":"1261-1293"},"PeriodicalIF":35.6,"publicationDate":"2023-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9739/10130694/10066875.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49952788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-10DOI: 10.1109/COMST.2023.3274934
Mohammed Jouhari;Nasir Saeed;Mohamed-Slim Alouini;El Mehdi Amhoud
Long-range (LoRa) technology is most widely used for enabling low-power wide area networks (WANs) on unlicensed frequency bands. Despite its modest data rates, it provides extensive coverage for low-power devices, making it an ideal communication system for many Internet of Things (IoT) applications. In general, LoRa is considered as the physical layer, whereas LoRaWAN is the medium access control (MAC) layer of the LoRa stack that adopts a star topology to enable communication between multiple end devices (EDs) and the network gateway. The chirp spread spectrum modulation deals with LoRa signal interference and ensures long-range communication. At the same time, the adaptive data rate mechanism allows EDs to dynamically alter some LoRa features, such as the spreading factor (SF), code rate, and carrier frequency to address the time variance of communication conditions in dense networks. Despite the high LoRa connectivity demand, LoRa signals interference and concurrent transmission collisions are major limitations. Therefore, to enhance LoRaWAN capacity, the LoRa Alliance released many LoRaWAN versions, and the research community has provided numerous solutions to develop scalable LoRaWAN technology. Hence, we thoroughly examine LoRaWAN scalability challenges and state-of-the-art solutions in both the physical and MAC layers. These solutions primarily rely on SF, logical, and frequency channel assignment, whereas others propose new network topologies or implement signal processing schemes to cancel the interference and allow LoRaWAN to connect more EDs efficiently. A summary of the existing solutions in the literature is provided at the end of the paper, describing the advantages and disadvantages of each solution and suggesting possible enhancements as future research directions.
{"title":"A Survey on Scalable LoRaWAN for Massive IoT: Recent Advances, Potentials, and Challenges","authors":"Mohammed Jouhari;Nasir Saeed;Mohamed-Slim Alouini;El Mehdi Amhoud","doi":"10.1109/COMST.2023.3274934","DOIUrl":"https://doi.org/10.1109/COMST.2023.3274934","url":null,"abstract":"Long-range (LoRa) technology is most widely used for enabling low-power wide area networks (WANs) on unlicensed frequency bands. Despite its modest data rates, it provides extensive coverage for low-power devices, making it an ideal communication system for many Internet of Things (IoT) applications. In general, LoRa is considered as the physical layer, whereas LoRaWAN is the medium access control (MAC) layer of the LoRa stack that adopts a star topology to enable communication between multiple end devices (EDs) and the network gateway. The chirp spread spectrum modulation deals with LoRa signal interference and ensures long-range communication. At the same time, the adaptive data rate mechanism allows EDs to dynamically alter some LoRa features, such as the spreading factor (SF), code rate, and carrier frequency to address the time variance of communication conditions in dense networks. Despite the high LoRa connectivity demand, LoRa signals interference and concurrent transmission collisions are major limitations. Therefore, to enhance LoRaWAN capacity, the LoRa Alliance released many LoRaWAN versions, and the research community has provided numerous solutions to develop scalable LoRaWAN technology. Hence, we thoroughly examine LoRaWAN scalability challenges and state-of-the-art solutions in both the physical and MAC layers. These solutions primarily rely on SF, logical, and frequency channel assignment, whereas others propose new network topologies or implement signal processing schemes to cancel the interference and allow LoRaWAN to connect more EDs efficiently. A summary of the existing solutions in the literature is provided at the end of the paper, describing the advantages and disadvantages of each solution and suggesting possible enhancements as future research directions.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"25 3","pages":"1841-1876"},"PeriodicalIF":35.6,"publicationDate":"2023-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49963515","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 : 2023-03-10DOI: 10.1109/COMST.2023.3275038
Yeongjae Kim
Over the last two decades, IEEE has been defining standards for Time-Sensitive Networking (TSN). These standards combine traffic shaping and scheduling mechanisms to guarantee bounded delays across an Ethernet network. Time-Sensitive Networks are designed for applications where delays are critical, such as process control, networks for vehicles and aircraft, and virtual reality applications. Many industrial companies are currently actively implementing TSN standards. The goal of this paper is to provide a concise and self-contained description of the TSN mechanisms and how they affect the network performance metrics. The paper is intended for practicing engineers wanting to improve their understanding of TSN and for students curious about these mechanisms.
{"title":"A Concise Tutorial on Traffic Shaping and Scheduling in Time-Sensitive Networks","authors":"Yeongjae Kim","doi":"10.1109/COMST.2023.3275038","DOIUrl":"https://doi.org/10.1109/COMST.2023.3275038","url":null,"abstract":"Over the last two decades, IEEE has been defining standards for Time-Sensitive Networking (TSN). These standards combine traffic shaping and scheduling mechanisms to guarantee bounded delays across an Ethernet network. Time-Sensitive Networks are designed for applications where delays are critical, such as process control, networks for vehicles and aircraft, and virtual reality applications. Many industrial companies are currently actively implementing TSN standards. The goal of this paper is to provide a concise and self-contained description of the TSN mechanisms and how they affect the network performance metrics. The paper is intended for practicing engineers wanting to improve their understanding of TSN and for students curious about these mechanisms.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"25 3","pages":"1941-1953"},"PeriodicalIF":35.6,"publicationDate":"2023-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49963700","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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