Pub Date : 2023-12-01DOI: 10.1109/MCOMSTD.0006.2300009
Farshad Miramirkhani, T. Baykaş, M. Elamassie, Murat Uysal
Increasing industrial attention to visible light communications (VLC) technology led the IEEE 802.11 to establish the task group 802.11bb “Light Communications” (LC) for the development of a VLC standard. As a part of the standard development process, the development of realistic channel models according to possible use cases is of critical importance for physical layer system design. This article presents the reference channel models for the mandatory usage models adopted by IEEE 802.11bb for the evaluation of system proposals. The use cases include industrial, medical, enterprise, and residential scenarios. Channel impulse responses and corresponding frequency responses are obtained for each use case using a ray tracing approach based on realistic specifications for transmitters and receivers, and optical characterization of the environment.
{"title":"IEEE 802.11BB Reference Channel Models For Light Communications","authors":"Farshad Miramirkhani, T. Baykaş, M. Elamassie, Murat Uysal","doi":"10.1109/MCOMSTD.0006.2300009","DOIUrl":"https://doi.org/10.1109/MCOMSTD.0006.2300009","url":null,"abstract":"Increasing industrial attention to visible light communications (VLC) technology led the IEEE 802.11 to establish the task group 802.11bb “Light Communications” (LC) for the development of a VLC standard. As a part of the standard development process, the development of realistic channel models according to possible use cases is of critical importance for physical layer system design. This article presents the reference channel models for the mandatory usage models adopted by IEEE 802.11bb for the evaluation of system proposals. The use cases include industrial, medical, enterprise, and residential scenarios. Channel impulse responses and corresponding frequency responses are obtained for each use case using a ray tracing approach based on realistic specifications for transmitters and receivers, and optical characterization of the environment.","PeriodicalId":36719,"journal":{"name":"IEEE Communications Standards Magazine","volume":"170 ","pages":"84-89"},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138992819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-01DOI: 10.1109/MCOMSTD.0002.2200004
Guillermo Pocovi, Renato Abreu, Pilar Andres, M. Deghel, Klaus Hugl, Thomas Jacobsen, Keeth Jayasinghe, Petteri Kela, Juha Korhonen, Ping-Heng Kuo, Lauri Kuru, Zexian Li, Timo Lunttila, Elena Peralta-Calvo, Claudio Rosa, Tao Tao
The 5G new radio (NR) standard has been designed since its initial release - 3GPP Release 15 - to support ultra-reliable low-latency communications (URLLC) requiring one-way down-link (DL) or uplink (UL) user-plane latencies of 1 ms with reliability of at least 99.999 percent. The following releases - Release 16 and 17- have further raised the bar, not only by offering further reduced latencies down to 0.5 ms and increased reliability up to 99.99999 percent, but also by supporting new industrial internet of things (IIoT) use cases demanding - among other things - time synchronization with 1 µs accuracy. This article provides an overview of the latest IIoT and URLLC-related enhancements adopted in the 5G NR standard, with focus on the recently standardized Release 17 features. This includes enhancements to the hybrid automatic repeat request (HARQ) and channel quality indicator (CQI) feed-back from the UE, propagation delay compensation for more accurate time synchronization, reliability and latency enhancements tailored to deployments on unlicensed bands, and scheduling optimizations taking into account different traffic priorities and higher-layer requirements of the industrial applications. Example performance results show how NR Release 17 offers improved performance over a wider range of deployment scenarios and frequency bands. Finally, an out-look toward expected URLLC and IIoT enhancements in future releases is provided.
{"title":"Further Enhanced Urllc And Industrial IoT Support With Release-17 5g New Radio","authors":"Guillermo Pocovi, Renato Abreu, Pilar Andres, M. Deghel, Klaus Hugl, Thomas Jacobsen, Keeth Jayasinghe, Petteri Kela, Juha Korhonen, Ping-Heng Kuo, Lauri Kuru, Zexian Li, Timo Lunttila, Elena Peralta-Calvo, Claudio Rosa, Tao Tao","doi":"10.1109/MCOMSTD.0002.2200004","DOIUrl":"https://doi.org/10.1109/MCOMSTD.0002.2200004","url":null,"abstract":"The 5G new radio (NR) standard has been designed since its initial release - 3GPP Release 15 - to support ultra-reliable low-latency communications (URLLC) requiring one-way down-link (DL) or uplink (UL) user-plane latencies of 1 ms with reliability of at least 99.999 percent. The following releases - Release 16 and 17- have further raised the bar, not only by offering further reduced latencies down to 0.5 ms and increased reliability up to 99.99999 percent, but also by supporting new industrial internet of things (IIoT) use cases demanding - among other things - time synchronization with 1 µs accuracy. This article provides an overview of the latest IIoT and URLLC-related enhancements adopted in the 5G NR standard, with focus on the recently standardized Release 17 features. This includes enhancements to the hybrid automatic repeat request (HARQ) and channel quality indicator (CQI) feed-back from the UE, propagation delay compensation for more accurate time synchronization, reliability and latency enhancements tailored to deployments on unlicensed bands, and scheduling optimizations taking into account different traffic priorities and higher-layer requirements of the industrial applications. Example performance results show how NR Release 17 offers improved performance over a wider range of deployment scenarios and frequency bands. Finally, an out-look toward expected URLLC and IIoT enhancements in future releases is provided.","PeriodicalId":36719,"journal":{"name":"IEEE Communications Standards Magazine","volume":"14 1","pages":"12-19"},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138992869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-01DOI: 10.1109/MCOMSTD.0001.2100081
Zhihan Lyu, Dongliang Chen, Haibin Lv
This work intends to improve ultra-reliable and low-latency communication (URLLC) service in space-air-ground integrated (SAGIN) and the network's quality of service. To this end, this work considers the queuing latency and transmission reliability of uplink and downlink networks. It also proposes an intelligent coordinated scheduling algorithm (ICSA) based on the adaptive Particle Swarm Optimization algorithm. The simulation experiment proves that ICSA achieves the optimal total priority and completion rate when scheduling different numbers of tasks. In addition, the time-slot Areal Locations of Hazardous Atmospheres protocol is applied to reduce URLLC's control-plane latency. With 100 or fewer tasks, the network resources can be scheduled with ease. Under the two transmission states, the Preamble Reservation Scheme is designed to provide timely URLLC services. As a result, the URLLC's random-access probability decreases as the number of URLLC requests increases. The results have vital significance for standardizing and promoting the URLLC service in the Sixth Generation Mobile Communication era.
{"title":"Space-air-ground Integrated Networks For Urllc In Spatial Digital Twins","authors":"Zhihan Lyu, Dongliang Chen, Haibin Lv","doi":"10.1109/MCOMSTD.0001.2100081","DOIUrl":"https://doi.org/10.1109/MCOMSTD.0001.2100081","url":null,"abstract":"This work intends to improve ultra-reliable and low-latency communication (URLLC) service in space-air-ground integrated (SAGIN) and the network's quality of service. To this end, this work considers the queuing latency and transmission reliability of uplink and downlink networks. It also proposes an intelligent coordinated scheduling algorithm (ICSA) based on the adaptive Particle Swarm Optimization algorithm. The simulation experiment proves that ICSA achieves the optimal total priority and completion rate when scheduling different numbers of tasks. In addition, the time-slot Areal Locations of Hazardous Atmospheres protocol is applied to reduce URLLC's control-plane latency. With 100 or fewer tasks, the network resources can be scheduled with ease. Under the two transmission states, the Preamble Reservation Scheme is designed to provide timely URLLC services. As a result, the URLLC's random-access probability decreases as the number of URLLC requests increases. The results have vital significance for standardizing and promoting the URLLC service in the Sixth Generation Mobile Communication era.","PeriodicalId":36719,"journal":{"name":"IEEE Communications Standards Magazine","volume":"171 ","pages":"6-11"},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139016777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-01DOI: 10.1109/MCOMSTD.0006.2300003
N. Abuali, Muhammad Bilal Khan, Mohammad Hayajneh, Mubashir Rehman
E-Health applications have recently become a popular topic in academia and industry. E-health has improved several key aspects of conventional healthcare paradigms due to its interdisciplinary approach. Furthermore, it facilitates an easier connection between the patient and the hospital, allowing E-health-based applications and public services to be accessed more efficiently. How-ever, the current reliance of E-health services on invasive sensing systems has been attributed to rising diseases, pandemics, costs, and well-being. Non-invasive sensing was selected as a possible solution to this problem because of its innate ability to improve containment, comfortability, privacy protection, and efficiency. Existing non-invasive sensing research studies exploit wireless communication systems having portability, adaptability, and flexibility issues for large-scale implementation to provide cost-effective, intelligent health-care services. This article discusses non-invasive sensing challenges for E-health applications using wireless communication systems, and proposes a software-defined radio frequency (SDRF) sensing system. The integration of advanced signal processing (SP) and artificial intelligence (AI) techniques with SDRF sensing systems has the potential to overcome the challenges of existing wireless communication-based systems and meet the demands of massive E-Health applications.
{"title":"Exploiting Wireless Communication Using Software-defined Radio Frequency Sensing For E-health APPLICATIONS","authors":"N. Abuali, Muhammad Bilal Khan, Mohammad Hayajneh, Mubashir Rehman","doi":"10.1109/MCOMSTD.0006.2300003","DOIUrl":"https://doi.org/10.1109/MCOMSTD.0006.2300003","url":null,"abstract":"E-Health applications have recently become a popular topic in academia and industry. E-health has improved several key aspects of conventional healthcare paradigms due to its interdisciplinary approach. Furthermore, it facilitates an easier connection between the patient and the hospital, allowing E-health-based applications and public services to be accessed more efficiently. How-ever, the current reliance of E-health services on invasive sensing systems has been attributed to rising diseases, pandemics, costs, and well-being. Non-invasive sensing was selected as a possible solution to this problem because of its innate ability to improve containment, comfortability, privacy protection, and efficiency. Existing non-invasive sensing research studies exploit wireless communication systems having portability, adaptability, and flexibility issues for large-scale implementation to provide cost-effective, intelligent health-care services. This article discusses non-invasive sensing challenges for E-health applications using wireless communication systems, and proposes a software-defined radio frequency (SDRF) sensing system. The integration of advanced signal processing (SP) and artificial intelligence (AI) techniques with SDRF sensing systems has the potential to overcome the challenges of existing wireless communication-based systems and meet the demands of massive E-Health applications.","PeriodicalId":36719,"journal":{"name":"IEEE Communications Standards Magazine","volume":"202 1","pages":"42-48"},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139025036","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-01DOI: 10.1109/MCOMSTD.0005.2200070
Xingqin Lin, Lopamudra Kundu, Chris Dick, Soma Velayutham
Artificial intelligence (AI) has emerged as a powerful technology that improves system performance and enables new features in 5G and beyond. Standardization - defining functionality and interfaces - is essential for driving the industry alignment required to deliver the mass adoption of AI in 5G-Advanced and 6G. However, fragmented efforts in different standards bodies, such as the 3rd Generation Partnership Project (3GPP) and the Open Radio Access Network (O-RAN) Alliance, can lead to confusion and uncertainty about which standards to follow and which aspects of the standards to embrace. This article provides a joint 3GPP and O-RAN perspective on the state of the art in AI adoption in mobile communication systems, including the fundamentals of 5G architecture and its evolution toward openness and intelligence, AI for 5G-Advanced evolution and open RAN, and a case study on AI-enabled traffic steering. We also identify several areas for future exploration to accelerate AI adoption on the path toward 6G.
{"title":"Embracing Ai In 5g-advanced Toward 6g: A JOINT 3GPP AND O-RAN Perspective","authors":"Xingqin Lin, Lopamudra Kundu, Chris Dick, Soma Velayutham","doi":"10.1109/MCOMSTD.0005.2200070","DOIUrl":"https://doi.org/10.1109/MCOMSTD.0005.2200070","url":null,"abstract":"Artificial intelligence (AI) has emerged as a powerful technology that improves system performance and enables new features in 5G and beyond. Standardization - defining functionality and interfaces - is essential for driving the industry alignment required to deliver the mass adoption of AI in 5G-Advanced and 6G. However, fragmented efforts in different standards bodies, such as the 3rd Generation Partnership Project (3GPP) and the Open Radio Access Network (O-RAN) Alliance, can lead to confusion and uncertainty about which standards to follow and which aspects of the standards to embrace. This article provides a joint 3GPP and O-RAN perspective on the state of the art in AI adoption in mobile communication systems, including the fundamentals of 5G architecture and its evolution toward openness and intelligence, AI for 5G-Advanced evolution and open RAN, and a case study on AI-enabled traffic steering. We also identify several areas for future exploration to accelerate AI adoption on the path toward 6G.","PeriodicalId":36719,"journal":{"name":"IEEE Communications Standards Magazine","volume":"189 ","pages":"76-83"},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139021571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-01DOI: 10.1109/MCOMSTD.0005.2200077
Yaoqi Yang, Bangning Zhang, D. Guo, Weizheng Wang, Xingwang Li, Chunqiang Hu
Mobile crowdsensing (MCS) is an effective and timely sensing data collection manner. Privacy preservation and data freshness are the two biggest concerns for the robust MCS in the modern era. Data encryption and age of information (Aol) optimization technologies can help current MCS alleviate these two issues by processing a great volume of data messages with strong security and minimal delay. In this article, a secure and timely MCS framework (PPFO: privacy preservationori-ented data freshness optimization) is put forward to achieve the privacy preservation and data freshness optimization, that is, Aol minimization on the five-layer architecture. Particularly in the link and operation layers privacy preservation is realized by an encryption approach. Game theory methodology provides a solution to Aol optimization in the perception and transmission layers. Finally, the numerical results have shown the feasibility and effectiveness of the proposed framework.
{"title":"PPFO: A Privacy Preservation-oriented Data Freshness Optimization Framework For Mobile Crowdsensing","authors":"Yaoqi Yang, Bangning Zhang, D. Guo, Weizheng Wang, Xingwang Li, Chunqiang Hu","doi":"10.1109/MCOMSTD.0005.2200077","DOIUrl":"https://doi.org/10.1109/MCOMSTD.0005.2200077","url":null,"abstract":"Mobile crowdsensing (MCS) is an effective and timely sensing data collection manner. Privacy preservation and data freshness are the two biggest concerns for the robust MCS in the modern era. Data encryption and age of information (Aol) optimization technologies can help current MCS alleviate these two issues by processing a great volume of data messages with strong security and minimal delay. In this article, a secure and timely MCS framework (PPFO: privacy preservationori-ented data freshness optimization) is put forward to achieve the privacy preservation and data freshness optimization, that is, Aol minimization on the five-layer architecture. Particularly in the link and operation layers privacy preservation is realized by an encryption approach. Game theory methodology provides a solution to Aol optimization in the perception and transmission layers. Finally, the numerical results have shown the feasibility and effectiveness of the proposed framework.","PeriodicalId":36719,"journal":{"name":"IEEE Communications Standards Magazine","volume":"8 ","pages":"34-40"},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139026297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Electronic voting systems have undergone several studies to ensure the reliability of results. Many approaches have since been suggested to solve ongoing problems, including the adoption of conventional cryptographic techniques. On the one hand, the transfers of electronic voting data over Internet protocol-based Internet are vulnerable to numerous security and privacy attacks. On the other hand, named data networking (NDN) and 6G are interesting areas for the future Internet paradigm, aiming to cope with the short-comings of the conventional host-based Internet paradigm. NDNs are designed to provide network caching, mobility, and named-based routing for the efficient information access of end-users. Quantum communication is an alternative technology with excessive application potential in 6G networks. Consequently, substantial progress has been achieved in developing quantum cryptography for quantum communications to surge the privacy, reliability, and security of data transmission. This study aims to determine the applicability of electronic voting systems with NDN and 6G technology by presenting a novel architecture to enhance applications, ensure security, and gratify mobility.
{"title":"A Secure Ndn-based Architecture For Electronic Voting In 6g","authors":"Syed Sajid Ullah, Saddam Hussain, Ihsan Ali, Spyridon Mastorakis","doi":"10.1109/MCOMSTD.0003.2200074","DOIUrl":"https://doi.org/10.1109/MCOMSTD.0003.2200074","url":null,"abstract":"Electronic voting systems have undergone several studies to ensure the reliability of results. Many approaches have since been suggested to solve ongoing problems, including the adoption of conventional cryptographic techniques. On the one hand, the transfers of electronic voting data over Internet protocol-based Internet are vulnerable to numerous security and privacy attacks. On the other hand, named data networking (NDN) and 6G are interesting areas for the future Internet paradigm, aiming to cope with the short-comings of the conventional host-based Internet paradigm. NDNs are designed to provide network caching, mobility, and named-based routing for the efficient information access of end-users. Quantum communication is an alternative technology with excessive application potential in 6G networks. Consequently, substantial progress has been achieved in developing quantum cryptography for quantum communications to surge the privacy, reliability, and security of data transmission. This study aims to determine the applicability of electronic voting systems with NDN and 6G technology by presenting a novel architecture to enhance applications, ensure security, and gratify mobility.","PeriodicalId":36719,"journal":{"name":"IEEE Communications Standards Magazine","volume":"35 5","pages":"20-26"},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139013380","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-01DOI: 10.1109/MCOMSTD.0004.2200076
Alekha Kumar Mishra, Deepak Puthal
Federated learning collects data from various devices, analyzes it locally, aggregates it, and then finds meaningful insights from it. Data sampling works the same way by dividing the larger data set into smaller parts and applying computation to those data sets, which reduces the time taken to do the work. Data sampling in federated learning aims to find the ideal mixture of selecting data sets for training purposes to improve training accuracy while staying within the maximum capability of the device and network. In this article, we present an overview and analysis of recent data sampling techniques for federated learning. The list includes sampling approaches suitable for federated learning environments such as clustering, dynamic sampling, adaptive sampling, probabilistic sampling, and many more. The feature analysis is comprised of a description of the procedure, the criteria, and other relevant parameters for sampling. The efficiency of the sampling technique is analyzed via comparison of claimed accuracy and convergence rate with respect to the used dataset.
{"title":"Data Sampling In Federated Learning: Principles, Features And Taxonomy","authors":"Alekha Kumar Mishra, Deepak Puthal","doi":"10.1109/MCOMSTD.0004.2200076","DOIUrl":"https://doi.org/10.1109/MCOMSTD.0004.2200076","url":null,"abstract":"Federated learning collects data from various devices, analyzes it locally, aggregates it, and then finds meaningful insights from it. Data sampling works the same way by dividing the larger data set into smaller parts and applying computation to those data sets, which reduces the time taken to do the work. Data sampling in federated learning aims to find the ideal mixture of selecting data sets for training purposes to improve training accuracy while staying within the maximum capability of the device and network. In this article, we present an overview and analysis of recent data sampling techniques for federated learning. The list includes sampling approaches suitable for federated learning environments such as clustering, dynamic sampling, adaptive sampling, probabilistic sampling, and many more. The feature analysis is comprised of a description of the procedure, the criteria, and other relevant parameters for sampling. The efficiency of the sampling technique is analyzed via comparison of claimed accuracy and convergence rate with respect to the used dataset.","PeriodicalId":36719,"journal":{"name":"IEEE Communications Standards Magazine","volume":"799 ","pages":"28-33"},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139024774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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