Pub Date : 2022-10-01DOI: 10.1109/FNWF55208.2022.00105
H. Zaglauer, Arturs Lindenbergs, M. Lankinen, K. Kaare, Kristjan Kuhi, Miquel Payaró
The 5G-ROUTES project is part of the European effort to validate, test and pre-deploy 5G connectivity along major transport corridors with a focus on cross-border segments. It addresses Connected and Automated Mobility applications along the ‘Via Baltica North’ traversing Finland, Estonia, and Latvia and, also, 5G connectivity across the Baltic Sea between Finland and Estonia. The signal strength of coastal base stations both in the 700 MHz and 3.5 GHz frequency was measured along the ferry route between the ports of Helsinki/Vuosaari in Finland and Tallinn/Muuga in Estonia. Even though the 5G signals could be detected much further away from the coast than expected, there remains a gap in coverage that needs to be closed to provide continuous 5G connectivity of sufficient bandwidth. The installation of communication infrastructure along water ways is challenging and impossible in some areas, therefore the 5G-ROUTES project has investigated innovative approaches such as various multi-hop concepts and the use of satellites. In the planned trial phase, selected solutions shall be field tested and demonstrated to evaluate their suitability, technical maturity and performance. The obtained results of the 5G-ROUTES ferry trials will be applicable also to much longer ferry routes and can be transferred to road and rail transport in very remote areas where deployment of suitable 5G infrastructure may be technologically challenging and costly.
{"title":"Providing Continuous 5G Connectivity along Ferry Lines – Concepts and Trials of 5G-ROUTES Project (Invited paper)","authors":"H. Zaglauer, Arturs Lindenbergs, M. Lankinen, K. Kaare, Kristjan Kuhi, Miquel Payaró","doi":"10.1109/FNWF55208.2022.00105","DOIUrl":"https://doi.org/10.1109/FNWF55208.2022.00105","url":null,"abstract":"The 5G-ROUTES project is part of the European effort to validate, test and pre-deploy 5G connectivity along major transport corridors with a focus on cross-border segments. It addresses Connected and Automated Mobility applications along the ‘Via Baltica North’ traversing Finland, Estonia, and Latvia and, also, 5G connectivity across the Baltic Sea between Finland and Estonia. The signal strength of coastal base stations both in the 700 MHz and 3.5 GHz frequency was measured along the ferry route between the ports of Helsinki/Vuosaari in Finland and Tallinn/Muuga in Estonia. Even though the 5G signals could be detected much further away from the coast than expected, there remains a gap in coverage that needs to be closed to provide continuous 5G connectivity of sufficient bandwidth. The installation of communication infrastructure along water ways is challenging and impossible in some areas, therefore the 5G-ROUTES project has investigated innovative approaches such as various multi-hop concepts and the use of satellites. In the planned trial phase, selected solutions shall be field tested and demonstrated to evaluate their suitability, technical maturity and performance. The obtained results of the 5G-ROUTES ferry trials will be applicable also to much longer ferry routes and can be transferred to road and rail transport in very remote areas where deployment of suitable 5G infrastructure may be technologically challenging and costly.","PeriodicalId":300165,"journal":{"name":"2022 IEEE Future Networks World Forum (FNWF)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125360128","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 : 2022-10-01DOI: 10.1109/FNWF55208.2022.00013
Selva Via, Miquel Payaró, Kurt Eckert, Maciej Mühleisen, Stefan Wendt, Edwin Fischer, D. Hetzer, A. Kousaridas
The 5GCroCo project conducted large-scale trials of 5G technologies for Connected and Automated Mobility (CAM) in two road corridors along the border areas in France-Germany and Luxembourg-Germany. In this context, this paper provides a succinct description of a subset of the key 5G technologies that have been trialed and highlights representative experimental results that have been obtained for three CAM use cases with a clear focus of achieving seamless service continuity along cross-border and showing the benefits of 5G in comparison to 4G. The trial results provide an experimental validation of the feasibility of the technical solutions proposed, developed, and used in the project.
{"title":"5GCroCo: Key 5G technologies and trial results for seamless cross-border CAM services (Invited Paper)","authors":"Selva Via, Miquel Payaró, Kurt Eckert, Maciej Mühleisen, Stefan Wendt, Edwin Fischer, D. Hetzer, A. Kousaridas","doi":"10.1109/FNWF55208.2022.00013","DOIUrl":"https://doi.org/10.1109/FNWF55208.2022.00013","url":null,"abstract":"The 5GCroCo project conducted large-scale trials of 5G technologies for Connected and Automated Mobility (CAM) in two road corridors along the border areas in France-Germany and Luxembourg-Germany. In this context, this paper provides a succinct description of a subset of the key 5G technologies that have been trialed and highlights representative experimental results that have been obtained for three CAM use cases with a clear focus of achieving seamless service continuity along cross-border and showing the benefits of 5G in comparison to 4G. The trial results provide an experimental validation of the feasibility of the technical solutions proposed, developed, and used in the project.","PeriodicalId":300165,"journal":{"name":"2022 IEEE Future Networks World Forum (FNWF)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129319475","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 : 2022-10-01DOI: 10.1109/FNWF55208.2022.00058
M. Corici, Fabian Eichhorn, V. Gowtham, T. Magedanz
Beyond 5G and 6G mobile network research gained a lot of traction in recent years. The German Open6GHub project funded by the German Federal Ministry of Education and Research (BMBF) is a recent project working on researching and developing technologies towards 6G networks. This article presents the Open6GHub view on the requirements and approaches of the networks of 2030 and beyond. At this early stage, we have the opportunity to investigate more fundamental changes within the system architecture of mobile networks. This article presents the architectural concept of Organic Networks and how it can drive the evolution of mobile networks towards a more adaptable, efficient, and resource and requirements oriented network. The Open6GHub consortium is one of the principal investigators and drivers behind the Organic Network concept.
{"title":"Drivers for Organic 6G Networking","authors":"M. Corici, Fabian Eichhorn, V. Gowtham, T. Magedanz","doi":"10.1109/FNWF55208.2022.00058","DOIUrl":"https://doi.org/10.1109/FNWF55208.2022.00058","url":null,"abstract":"Beyond 5G and 6G mobile network research gained a lot of traction in recent years. The German Open6GHub project funded by the German Federal Ministry of Education and Research (BMBF) is a recent project working on researching and developing technologies towards 6G networks. This article presents the Open6GHub view on the requirements and approaches of the networks of 2030 and beyond. At this early stage, we have the opportunity to investigate more fundamental changes within the system architecture of mobile networks. This article presents the architectural concept of Organic Networks and how it can drive the evolution of mobile networks towards a more adaptable, efficient, and resource and requirements oriented network. The Open6GHub consortium is one of the principal investigators and drivers behind the Organic Network concept.","PeriodicalId":300165,"journal":{"name":"2022 IEEE Future Networks World Forum (FNWF)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124798404","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 : 2022-10-01DOI: 10.1109/FNWF55208.2022.00118
F. Moscatelli, Thanos Xirofotos, Amr Rizk, Nehal Baganal-Krishna, E. Bonetto, Eirini Liotou, A. Amditis
The advent of 5G has been a game-changer in the Automotive Vertical sector. 5G acts as an enabler of advanced networking architectures which, in turn, allow the development of novel services, by attracting and engaging third parties to experiment using available 5G infrastructure and connectivity. 5G-IANA is a Horizon 2020 ICT-41 project that targets to create such an advanced open experimentation platform, bringing powerful novelty to third parties through the integration and provisioning of far-edge resources for network orchestration purposes, and through the offering of Machine Learning knowledge as an add-on service to them. The scope of this paper is, therefore, to present the 5G-IANA project overall goals, by emphasizing the most important expected innovations from the project regarding far-edge resources' orchestration and ML as a service provisioning.
{"title":"The 5G-IANA platform: Bringing far-edge resources and ML potential to the disposal of automotive third parties","authors":"F. Moscatelli, Thanos Xirofotos, Amr Rizk, Nehal Baganal-Krishna, E. Bonetto, Eirini Liotou, A. Amditis","doi":"10.1109/FNWF55208.2022.00118","DOIUrl":"https://doi.org/10.1109/FNWF55208.2022.00118","url":null,"abstract":"The advent of 5G has been a game-changer in the Automotive Vertical sector. 5G acts as an enabler of advanced networking architectures which, in turn, allow the development of novel services, by attracting and engaging third parties to experiment using available 5G infrastructure and connectivity. 5G-IANA is a Horizon 2020 ICT-41 project that targets to create such an advanced open experimentation platform, bringing powerful novelty to third parties through the integration and provisioning of far-edge resources for network orchestration purposes, and through the offering of Machine Learning knowledge as an add-on service to them. The scope of this paper is, therefore, to present the 5G-IANA project overall goals, by emphasizing the most important expected innovations from the project regarding far-edge resources' orchestration and ML as a service provisioning.","PeriodicalId":300165,"journal":{"name":"2022 IEEE Future Networks World Forum (FNWF)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128708132","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 : 2022-10-01DOI: 10.1109/FNWF55208.2022.00025
M. Kuzlu, Ferhat Ozgur Catak, S. Sarp, U. Cali, O. Gueler
With the rapid development and integration of artificial intelligence (AI) methods in next-generation networks (NextG), AI algorithms have provided significant advantages for NextG in terms of frequency spectrum usage, bandwidth, latency, and security. A key feature of NextG is the integration of AI, i.e., self-learning architecture based on self-supervised algorithms, to improve the performance of the network. A secure AI-powered structure is also expected to protect N extG networks against cyber-attacks. However, AI itself may be attacked, i.e., model poisoning targeted by attackers, and it results in cybersecurity violations. This paper proposes an AI trust platform using Streamlit for N extG networks that allows researchers to evaluate, defend, certify, and verify their AI models and applications against adversarial threats of evasion, poisoning, extraction, and interference.
{"title":"A Streamlit-based Artificial Intelligence Trust Platform for Next-Generation Wireless Networks","authors":"M. Kuzlu, Ferhat Ozgur Catak, S. Sarp, U. Cali, O. Gueler","doi":"10.1109/FNWF55208.2022.00025","DOIUrl":"https://doi.org/10.1109/FNWF55208.2022.00025","url":null,"abstract":"With the rapid development and integration of artificial intelligence (AI) methods in next-generation networks (NextG), AI algorithms have provided significant advantages for NextG in terms of frequency spectrum usage, bandwidth, latency, and security. A key feature of NextG is the integration of AI, i.e., self-learning architecture based on self-supervised algorithms, to improve the performance of the network. A secure AI-powered structure is also expected to protect N extG networks against cyber-attacks. However, AI itself may be attacked, i.e., model poisoning targeted by attackers, and it results in cybersecurity violations. This paper proposes an AI trust platform using Streamlit for N extG networks that allows researchers to evaluate, defend, certify, and verify their AI models and applications against adversarial threats of evasion, poisoning, extraction, and interference.","PeriodicalId":300165,"journal":{"name":"2022 IEEE Future Networks World Forum (FNWF)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126977466","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 : 2022-10-01DOI: 10.1109/FNWF55208.2022.00039
R. Chaparadza, Muslim Elkotob, Benoit Radier, T. B. Meriem, Eman M. Hammad, T. Choi
Future Networks, Beyond 5G and 6G, will continue to expand in scale, complexity and interconnectivity, and will be highly shaped by distributed systems that serve various use cases that go beyond current Use Cases like mMTC (massive Machine Type Communications) and URLLC (Ultra Reliable Low Latency Communications). This will be coupled with an increasing demand for autonomy in self-organization and self-management, automation and interoperability on a very dynamic flexible basis. Systems-of-systems architectures will become more relevant as multiple autonomous/semi-autonomous systems adaptively seek to operate and interact with their peers (including in the advent of so-called “symbiotic autonomous systems”). Research on autonomous systems and autonomic networks recognizes the benefits to making autonomic/autonomous systems interact with each other when needed and should explore frameworks that will enable this dynamic interactivity under the emerging concept of Federation of Autonomic/Autonomous networks (ANs). Autonomy and Degree of Autonomy in ANs should be subjected to “governance by humans” through their exposure of Governance Interfaces to make sure ANs solely serve purposes that humans expect of them and not negatively impact environment and society. The use of Federation and in some cases Governance interfaces and mechanisms is a promising technology for interconnecting systems, enabling innovation and service delivery by the federating AN systems; and allowing asset sharing and extending traditional eco-systems and value-chains with further resources and stakeholders (including new ones that were never involved in the traditional ICT ecosystems but should now be involved in 5G and 6G ecosystems). The paper provides an analysis of the aspects of relevance to the broader picture of ANs in standardization efforts, multi-layer autonomic systems design and operational principles, federation and governance of ANs, progress and open challenges in standards, so as to provide contributions on what needs to be complemented to ongoing efforts in standardization groups. This paper also serves to give an analysis of progress in key topics of the IEEE workshop held on this subject (of which the paper contributed).
{"title":"Autonomic/Autonomous Networking (AN): Federations & Governance of ANs, Progress & Open Challenges in Standards: Analysis Report","authors":"R. Chaparadza, Muslim Elkotob, Benoit Radier, T. B. Meriem, Eman M. Hammad, T. Choi","doi":"10.1109/FNWF55208.2022.00039","DOIUrl":"https://doi.org/10.1109/FNWF55208.2022.00039","url":null,"abstract":"Future Networks, Beyond 5G and 6G, will continue to expand in scale, complexity and interconnectivity, and will be highly shaped by distributed systems that serve various use cases that go beyond current Use Cases like mMTC (massive Machine Type Communications) and URLLC (Ultra Reliable Low Latency Communications). This will be coupled with an increasing demand for autonomy in self-organization and self-management, automation and interoperability on a very dynamic flexible basis. Systems-of-systems architectures will become more relevant as multiple autonomous/semi-autonomous systems adaptively seek to operate and interact with their peers (including in the advent of so-called “symbiotic autonomous systems”). Research on autonomous systems and autonomic networks recognizes the benefits to making autonomic/autonomous systems interact with each other when needed and should explore frameworks that will enable this dynamic interactivity under the emerging concept of Federation of Autonomic/Autonomous networks (ANs). Autonomy and Degree of Autonomy in ANs should be subjected to “governance by humans” through their exposure of Governance Interfaces to make sure ANs solely serve purposes that humans expect of them and not negatively impact environment and society. The use of Federation and in some cases Governance interfaces and mechanisms is a promising technology for interconnecting systems, enabling innovation and service delivery by the federating AN systems; and allowing asset sharing and extending traditional eco-systems and value-chains with further resources and stakeholders (including new ones that were never involved in the traditional ICT ecosystems but should now be involved in 5G and 6G ecosystems). The paper provides an analysis of the aspects of relevance to the broader picture of ANs in standardization efforts, multi-layer autonomic systems design and operational principles, federation and governance of ANs, progress and open challenges in standards, so as to provide contributions on what needs to be complemented to ongoing efforts in standardization groups. This paper also serves to give an analysis of progress in key topics of the IEEE workshop held on this subject (of which the paper contributed).","PeriodicalId":300165,"journal":{"name":"2022 IEEE Future Networks World Forum (FNWF)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122403162","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 : 2022-10-01DOI: 10.1109/FNWF55208.2022.00070
Mohamed Gaballa, M. Abbod, Sadeq Alnasur
In this paper, the influence of Deep Neural Network (DNN) in predicting both the channel parameters and the power factors for users in a Power Domain Multi-Input Single-Output Non-Orthogonal Multiple Access (MISO-NOMA) system is inspected. In channel prediction based Deep Learning (DL) approach, we integrate the Long Short Term Memory (LSTM) learning network into NOMA system in order that LSTM can be utilized to predict the channel coefficients. In addition, in Deep Learning based power estimation method, we introduce an algorithm based on Convolutional Neural Network (CNN) to predict and allocate the power factor for each user in MISO-NOMA cell. DNN is trained online using channel statistics in order to approximate the channel coefficients and allocate the power factors for each user, so that these parameters can be utilized by the receiver to recover the desired data. Besides, this paper demonstrates the framework where channel prediction based on LSTM layer and power approximation based on CNN can be jointly employed for multiuser detection in MISO-NOMA. In this work, Power factors are optimized analytically based on maximizing the sum-rate of users to derive the optimum power factors. Simulation outcomes for distinct metrics have verified the dominance of the channel estimation and power predication based DNN over standard approaches.
{"title":"Hybrid Deep Learning for Channel Estimation and Power Allocation for MISO-NOMA System","authors":"Mohamed Gaballa, M. Abbod, Sadeq Alnasur","doi":"10.1109/FNWF55208.2022.00070","DOIUrl":"https://doi.org/10.1109/FNWF55208.2022.00070","url":null,"abstract":"In this paper, the influence of Deep Neural Network (DNN) in predicting both the channel parameters and the power factors for users in a Power Domain Multi-Input Single-Output Non-Orthogonal Multiple Access (MISO-NOMA) system is inspected. In channel prediction based Deep Learning (DL) approach, we integrate the Long Short Term Memory (LSTM) learning network into NOMA system in order that LSTM can be utilized to predict the channel coefficients. In addition, in Deep Learning based power estimation method, we introduce an algorithm based on Convolutional Neural Network (CNN) to predict and allocate the power factor for each user in MISO-NOMA cell. DNN is trained online using channel statistics in order to approximate the channel coefficients and allocate the power factors for each user, so that these parameters can be utilized by the receiver to recover the desired data. Besides, this paper demonstrates the framework where channel prediction based on LSTM layer and power approximation based on CNN can be jointly employed for multiuser detection in MISO-NOMA. In this work, Power factors are optimized analytically based on maximizing the sum-rate of users to derive the optimum power factors. Simulation outcomes for distinct metrics have verified the dominance of the channel estimation and power predication based DNN over standard approaches.","PeriodicalId":300165,"journal":{"name":"2022 IEEE Future Networks World Forum (FNWF)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121253242","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 : 2022-10-01DOI: 10.1109/FNWF55208.2022.00113
Morteza Kheirkhah, Ulises Olvera-Hernandez, T. Çogalan, Alain A. M. Mourad
This paper explores two new ideas to enable Artificial Intelligence (AI) and Machine Learning (ML) in 5G Systems, which is an essential need for modern networks, allowing users to utilize multiple access technologies (cellular and Wi-Fi) simultaneously. The first idea proposes to connect a meddler component so-called “Stack Data Analytics Coordinator” (SDAC), with each radio protocol stack (e.g., 5G-NR or Wi-Fi) at both user equipment (UE) and access network nodes (e.g., gNB and Wi-Fi AP/Controller). SDAC acts as a coordinator between data providers (which could be in a protocol stack) and analytics providers (which could be anywhere in the 5GS and UE). However, if an analytics consumer is within the protocol stack (e.g., at the MAC layer), then SDAC allows an analytics provider to be operating close to the protocol stack (e.g., at the same box), minimizing end-to-end communication latency between these components. Furthermore, SDACs allow UE, WLAN (Wireless LAN), RAN (Radio Access Network), and Core Network (CN) to directly interact with each other and exchange statistics, measurements, and analytics in a flexible manner (i.e., fast and with low overhead). Hence, they facilitate the AI/ML deployments within UE, RAN, WLAN, and CN. To realize SDAC, several new interfaces are defined, including Napp, Nsdac, Nwifi, and N5g. The second idea extends the network data analytics services concept, currently standardized in the 5G Core, into UE, RAN, and WLAN environments. This service expansion unifies the deployment of AI/ML techniques and also the way in which data and analytics should be stored and retrieved within UE, RAN, WLAN and CN. This way, e.g., an SDAC residing at RAN, close to a gNB, can interact with Network Data Analytics Functions (NWDAFs) operating in RAN, UE, and other locations.
{"title":"SDAC: An Architectural Enhancement to Enable Artificial Intelligence in 5G Systems","authors":"Morteza Kheirkhah, Ulises Olvera-Hernandez, T. Çogalan, Alain A. M. Mourad","doi":"10.1109/FNWF55208.2022.00113","DOIUrl":"https://doi.org/10.1109/FNWF55208.2022.00113","url":null,"abstract":"This paper explores two new ideas to enable Artificial Intelligence (AI) and Machine Learning (ML) in 5G Systems, which is an essential need for modern networks, allowing users to utilize multiple access technologies (cellular and Wi-Fi) simultaneously. The first idea proposes to connect a meddler component so-called “Stack Data Analytics Coordinator” (SDAC), with each radio protocol stack (e.g., 5G-NR or Wi-Fi) at both user equipment (UE) and access network nodes (e.g., gNB and Wi-Fi AP/Controller). SDAC acts as a coordinator between data providers (which could be in a protocol stack) and analytics providers (which could be anywhere in the 5GS and UE). However, if an analytics consumer is within the protocol stack (e.g., at the MAC layer), then SDAC allows an analytics provider to be operating close to the protocol stack (e.g., at the same box), minimizing end-to-end communication latency between these components. Furthermore, SDACs allow UE, WLAN (Wireless LAN), RAN (Radio Access Network), and Core Network (CN) to directly interact with each other and exchange statistics, measurements, and analytics in a flexible manner (i.e., fast and with low overhead). Hence, they facilitate the AI/ML deployments within UE, RAN, WLAN, and CN. To realize SDAC, several new interfaces are defined, including Napp, Nsdac, Nwifi, and N5g. The second idea extends the network data analytics services concept, currently standardized in the 5G Core, into UE, RAN, and WLAN environments. This service expansion unifies the deployment of AI/ML techniques and also the way in which data and analytics should be stored and retrieved within UE, RAN, WLAN and CN. This way, e.g., an SDAC residing at RAN, close to a gNB, can interact with Network Data Analytics Functions (NWDAFs) operating in RAN, UE, and other locations.","PeriodicalId":300165,"journal":{"name":"2022 IEEE Future Networks World Forum (FNWF)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122345149","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 : 2022-10-01DOI: 10.1109/FNWF55208.2022.00093
G. R. Tejerina, L. Mendes, R. A. Souza
Intelligent reflective surfaces (IRS) are considered major enabling technologies for the sixth-generation (6G) of cellular networks. Since its conception, a handful of research has been conducted to characterize this new channel over different fading models. Therefore, we here investigate the effects of $kappa-mu$ fading in IRS-empowered systems subjected to coherent and random phase shifts. To this end, we propose new exact and mathematically tractable expressions for the signal-to-noise ratio probability density function and cumulative distribution function of the referred system. These new formulations enabled the analysis of the exact outage and coverage probability and average bit error rate. Analytical results were confronted with Monte Carlo simulations, which indicated great adherence to the proposed schemes. Finally, we investigate the system performance over coherent and random phase schemes and the impact of the carrier frequency, the number of reflecting elements, and the distance between the IRS and the user.
{"title":"On the Exact Performance of IRS-Assisted Communications Under Random and Coherent Phase Shifts Over $kappa-mu$ Fading Channels","authors":"G. R. Tejerina, L. Mendes, R. A. Souza","doi":"10.1109/FNWF55208.2022.00093","DOIUrl":"https://doi.org/10.1109/FNWF55208.2022.00093","url":null,"abstract":"Intelligent reflective surfaces (IRS) are considered major enabling technologies for the sixth-generation (6G) of cellular networks. Since its conception, a handful of research has been conducted to characterize this new channel over different fading models. Therefore, we here investigate the effects of $kappa-mu$ fading in IRS-empowered systems subjected to coherent and random phase shifts. To this end, we propose new exact and mathematically tractable expressions for the signal-to-noise ratio probability density function and cumulative distribution function of the referred system. These new formulations enabled the analysis of the exact outage and coverage probability and average bit error rate. Analytical results were confronted with Monte Carlo simulations, which indicated great adherence to the proposed schemes. Finally, we investigate the system performance over coherent and random phase schemes and the impact of the carrier frequency, the number of reflecting elements, and the distance between the IRS and the user.","PeriodicalId":300165,"journal":{"name":"2022 IEEE Future Networks World Forum (FNWF)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122347896","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 : 2022-10-01DOI: 10.1109/FNWF55208.2022.00128
Bastiaan Wissingh, D. Ravesteijn, Ramon S. Schwartz
This paper presents field trial results of two combined use cases with different QoS requirements: (1) a transport vertical Smart Junction use case; and (2) a healthcare vertical Paramedic Support use case. We focus on slicing prioritization configured in the RAN, at the gNB level, to guarantee QoS requirements for the combined use cases. We deploy three slices: Transport, Health, and general purpose (Internet) traffic. Our trial results show, by analysing the throughput in the network, that RAN slicing is suitable for guaranteeing QoS requirements of multiple applications and services co-existing in the same 5G network.
{"title":"Validating 5G Standalone slicing advantages through a real life mobility scenario","authors":"Bastiaan Wissingh, D. Ravesteijn, Ramon S. Schwartz","doi":"10.1109/FNWF55208.2022.00128","DOIUrl":"https://doi.org/10.1109/FNWF55208.2022.00128","url":null,"abstract":"This paper presents field trial results of two combined use cases with different QoS requirements: (1) a transport vertical Smart Junction use case; and (2) a healthcare vertical Paramedic Support use case. We focus on slicing prioritization configured in the RAN, at the gNB level, to guarantee QoS requirements for the combined use cases. We deploy three slices: Transport, Health, and general purpose (Internet) traffic. Our trial results show, by analysing the throughput in the network, that RAN slicing is suitable for guaranteeing QoS requirements of multiple applications and services co-existing in the same 5G network.","PeriodicalId":300165,"journal":{"name":"2022 IEEE Future Networks World Forum (FNWF)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129188451","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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