Pub Date : 2023-06-06DOI: 10.1109/EuCNC/6GSummit58263.2023.10188286
S. P. Sanon, C. Lipps, H. Schotten
Fully Homomorphic Encryption (FHE) is a cryp-tographic technique that enables secure computation over en-crypted data. It has been considered as a promising solution to provide secure and privacy-preserving Fifth Generation (5G) wireless network traffic prediction. However, one of the main challenges of using FHE is the precision loss occurring during the homomorphic computations which can have an impact on network planning and optimization, Quality of Service (QoS) management, and security monitoring. Therefore, this paper discusses the effect of precision loss in 5G wireless network traffic prediction. The result of the underlying study provides experimental upper and lower bounds of the precision loss as well as the selection of an appropriate precision parameter to balance the trade-off between performance and computational cost. All practical FHE schemes are based on a mathematical problem that appears to be resistant to quantum computers meaning that the work in this paper will be valid for future wireless generations even in the quantum era.
{"title":"Fully Homomorphic Encryption: Precision Loss in Wireless Mobile Communication","authors":"S. P. Sanon, C. Lipps, H. Schotten","doi":"10.1109/EuCNC/6GSummit58263.2023.10188286","DOIUrl":"https://doi.org/10.1109/EuCNC/6GSummit58263.2023.10188286","url":null,"abstract":"Fully Homomorphic Encryption (FHE) is a cryp-tographic technique that enables secure computation over en-crypted data. It has been considered as a promising solution to provide secure and privacy-preserving Fifth Generation (5G) wireless network traffic prediction. However, one of the main challenges of using FHE is the precision loss occurring during the homomorphic computations which can have an impact on network planning and optimization, Quality of Service (QoS) management, and security monitoring. Therefore, this paper discusses the effect of precision loss in 5G wireless network traffic prediction. The result of the underlying study provides experimental upper and lower bounds of the precision loss as well as the selection of an appropriate precision parameter to balance the trade-off between performance and computational cost. All practical FHE schemes are based on a mathematical problem that appears to be resistant to quantum computers meaning that the work in this paper will be valid for future wireless generations even in the quantum era.","PeriodicalId":65870,"journal":{"name":"公共管理高层论坛","volume":"164 1","pages":"466-471"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86437246","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 : 2023-06-06DOI: 10.1109/EuCNC/6GSummit58263.2023.10188252
Christopher Mollén, Gábor Fodor, R. Baldemair, J. Huschke, Julia Vinogradova
Joint communication and sensing (JCAS) systems use the same spectrum, hardware and antenna resources to jointly provide spectrally efficient communication, localization and sensing services. While previous work has analyzed the performance of communication with connected objects and localization of unconnected (passive) objects, the joint positioning of both connected and passive objects is less studied. In this paper, we consider a JCAS cellular system using orthogonal frequency-division multiplexing, in which the uplink communication signal is scattered on a moving target towards multiple receiving base stations. In this setting, multistatic sensing by cooperating base stations makes it possible to position the moving target while also positioning the transmitting user equipment based on the received communication signal at the base stations. We propose a channel model that can characterize the propagation of both the communication and sensing signals, and algorithms that facilitate the estimation of direction of arrivals and range, which in turn enables the system to infer the positions of both the communicating user and the passive target. We also show some illustrative results from the algorithms that indicate what such joint positioning practically can look like.
{"title":"Joint Multistatic Sensing of Transmitter and Target in OFDM-Based JCAS System","authors":"Christopher Mollén, Gábor Fodor, R. Baldemair, J. Huschke, Julia Vinogradova","doi":"10.1109/EuCNC/6GSummit58263.2023.10188252","DOIUrl":"https://doi.org/10.1109/EuCNC/6GSummit58263.2023.10188252","url":null,"abstract":"Joint communication and sensing (JCAS) systems use the same spectrum, hardware and antenna resources to jointly provide spectrally efficient communication, localization and sensing services. While previous work has analyzed the performance of communication with connected objects and localization of unconnected (passive) objects, the joint positioning of both connected and passive objects is less studied. In this paper, we consider a JCAS cellular system using orthogonal frequency-division multiplexing, in which the uplink communication signal is scattered on a moving target towards multiple receiving base stations. In this setting, multistatic sensing by cooperating base stations makes it possible to position the moving target while also positioning the transmitting user equipment based on the received communication signal at the base stations. We propose a channel model that can characterize the propagation of both the communication and sensing signals, and algorithms that facilitate the estimation of direction of arrivals and range, which in turn enables the system to infer the positions of both the communicating user and the passive target. We also show some illustrative results from the algorithms that indicate what such joint positioning practically can look like.","PeriodicalId":65870,"journal":{"name":"公共管理高层论坛","volume":"47 1","pages":"144-149"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75066966","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 : 2023-06-06DOI: 10.1109/EuCNC/6GSummit58263.2023.10188265
Frank von Schoettler, Eike Lyczkowski, Z. Hua, Patrick Matalla, S. Randel
The advent of industry 4.0 sets high and divers requirements for wireless communications. Visible light communication (VLC) is a technology that is able to address a set of those requirements. Within the area of VLC, we focus on optical camera communication (OCC) with a light emitting diode (LED) as sender and a complementary metal-oxide-semiconductor (CMOS) image sensor as receiver. The rolling shutter mechanism of the CMOS image sensor allows the system to achieve higher symbol rate than the frame rate. However, the sampling frequency of the rolling shutter is an unknown parameter that varies between smartphone models and therefore needs to be estimated if the system is required to work with a wide range of CMOS cameras. In this work, a non-data aided (NDA) digital timing synchronization algorithm employing a rolling shutter image sensor was analyzed using a spectral approach for application in an OCC system. The algorithm viability and wide applicability was demonstrated using the cameras of six different smartphone models.
{"title":"Timing Synchronization for Smartphone-Based Optical Camera Communication","authors":"Frank von Schoettler, Eike Lyczkowski, Z. Hua, Patrick Matalla, S. Randel","doi":"10.1109/EuCNC/6GSummit58263.2023.10188265","DOIUrl":"https://doi.org/10.1109/EuCNC/6GSummit58263.2023.10188265","url":null,"abstract":"The advent of industry 4.0 sets high and divers requirements for wireless communications. Visible light communication (VLC) is a technology that is able to address a set of those requirements. Within the area of VLC, we focus on optical camera communication (OCC) with a light emitting diode (LED) as sender and a complementary metal-oxide-semiconductor (CMOS) image sensor as receiver. The rolling shutter mechanism of the CMOS image sensor allows the system to achieve higher symbol rate than the frame rate. However, the sampling frequency of the rolling shutter is an unknown parameter that varies between smartphone models and therefore needs to be estimated if the system is required to work with a wide range of CMOS cameras. In this work, a non-data aided (NDA) digital timing synchronization algorithm employing a rolling shutter image sensor was analyzed using a spectral approach for application in an OCC system. The algorithm viability and wide applicability was demonstrated using the cameras of six different smartphone models.","PeriodicalId":65870,"journal":{"name":"公共管理高层论坛","volume":"4 1","pages":"311-316"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74420307","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 : 2023-06-06DOI: 10.1109/EuCNC/6GSummit58263.2023.10188337
Anastasios-Stavros Charismiadis, Jorge Moratinos Salcines, D. Tsolkas, David Artunedo Guillen, Javier Garcia Rodrigo
The 3GPP Common API Framework (CAPIF) has been an integral part of the 3GPP SA6 specifications. It has been defined to facilitate the network core exposure, towards new application enablers of various vertical industries (including, Unmanned aerial systems, Edge data networks, Factories of the future, and Vehicular communication systems). Beyond its initial target, we believe that CAPIF can be used as a key standardized API-management framework for secure and interoperable interaction among any API providers and API consumers. In this direction, we developed the CAPIF services, and we provide them as open-source code. Beyond its full compliance with the specifications, our implementation is accompanied by test plans and ready to use templates. Finally, as a proof-of-concept evaluation, we describe how CAPIF services have been applied successfully to an event management system.
{"title":"The 3GPP Common API framework: Open-source release and application use cases","authors":"Anastasios-Stavros Charismiadis, Jorge Moratinos Salcines, D. Tsolkas, David Artunedo Guillen, Javier Garcia Rodrigo","doi":"10.1109/EuCNC/6GSummit58263.2023.10188337","DOIUrl":"https://doi.org/10.1109/EuCNC/6GSummit58263.2023.10188337","url":null,"abstract":"The 3GPP Common API Framework (CAPIF) has been an integral part of the 3GPP SA6 specifications. It has been defined to facilitate the network core exposure, towards new application enablers of various vertical industries (including, Unmanned aerial systems, Edge data networks, Factories of the future, and Vehicular communication systems). Beyond its initial target, we believe that CAPIF can be used as a key standardized API-management framework for secure and interoperable interaction among any API providers and API consumers. In this direction, we developed the CAPIF services, and we provide them as open-source code. Beyond its full compliance with the specifications, our implementation is accompanied by test plans and ready to use templates. Finally, as a proof-of-concept evaluation, we describe how CAPIF services have been applied successfully to an event management system.","PeriodicalId":65870,"journal":{"name":"公共管理高层论坛","volume":"9 1","pages":"472-477"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77428316","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 : 2023-06-06DOI: 10.1109/EuCNC/6GSummit58263.2023.10188314
Tautvydas Lisas, R. Fréin
Classical classifiers such as the Support Vector Classifier (SVC) struggle to accurately classify video Quality of Delivery (QoD) time-series due to the challenge in constructing suitable decision boundaries using small amounts of training data. We develop a technique that takes advantage of a quantum-classical hybrid infrastructure called Quantum-Enhanced Codecs (QEC). We evaluate a (1) purely classical, (2) hybrid kernel, and (3) purely quantum classifier for video QoD congestion classification, where congestion is either low, medium or high, using QoD measurements from a real networking test-bed. Findings show that the SVC performs the classification task 4% better in the low congestion state and the kernel method performs 6.1% and 10.1% better for the medium and high congestion states. Empirical evidence suggests that when the SVC is trained on a very low amount of data, the classification accuracy varies significantly depending on the quality of the training data, however, the variance in classification accuracy of quantum models is significantly lower. Classical video QoD classifiers benefit from the quantum data embedding techniques. They learn better decision regions using less training data.
{"title":"Quantum Classifiers for Video Quality Delivery","authors":"Tautvydas Lisas, R. Fréin","doi":"10.1109/EuCNC/6GSummit58263.2023.10188314","DOIUrl":"https://doi.org/10.1109/EuCNC/6GSummit58263.2023.10188314","url":null,"abstract":"Classical classifiers such as the Support Vector Classifier (SVC) struggle to accurately classify video Quality of Delivery (QoD) time-series due to the challenge in constructing suitable decision boundaries using small amounts of training data. We develop a technique that takes advantage of a quantum-classical hybrid infrastructure called Quantum-Enhanced Codecs (QEC). We evaluate a (1) purely classical, (2) hybrid kernel, and (3) purely quantum classifier for video QoD congestion classification, where congestion is either low, medium or high, using QoD measurements from a real networking test-bed. Findings show that the SVC performs the classification task 4% better in the low congestion state and the kernel method performs 6.1% and 10.1% better for the medium and high congestion states. Empirical evidence suggests that when the SVC is trained on a very low amount of data, the classification accuracy varies significantly depending on the quality of the training data, however, the variance in classification accuracy of quantum models is significantly lower. Classical video QoD classifiers benefit from the quantum data embedding techniques. They learn better decision regions using less training data.","PeriodicalId":65870,"journal":{"name":"公共管理高层论坛","volume":"94 1","pages":"448-453"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83574221","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 : 2023-06-06DOI: 10.1109/EuCNC/6GSummit58263.2023.10188245
Saeid Sheikhi, Panos Kostakos
The rapid expansion of 5G networks, coupled with the emergence of 6G technology, has highlighted the critical need for robust security measures to protect communication infrastructures. A primary security concern in 5G core networks is Distributed Denial of Service (DDoS) attacks, which target the GTP protocol. Conventional methods for detecting these attacks exhibit weaknesses and may struggle to effectively identify novel and undiscovered attacks. In this paper, we proposed a federated learning-based approach to detect DDoS attacks on the GTP protocol within a 5G core network. The suggested model leverages the collective intelligence of multiple devices to efficiently and privately identify DDoS attacks. Additionally, we have developed a 5G testbed architecture that simulates a sophisticated public network, making it ideal for evaluating AI-based security applications and testing the implementation and deployment of the proposed model. The results of our experiments demonstrate that the proposed unsupervised federated learning model effectively detects DDoS attacks on the 5G network while preserving the privacy of individual network data. This underscores the potential of federated learning in enhancing the security of 5G networks and beyond.
{"title":"DDoS attack detection using unsupervised federated learning for 5G networks and beyond","authors":"Saeid Sheikhi, Panos Kostakos","doi":"10.1109/EuCNC/6GSummit58263.2023.10188245","DOIUrl":"https://doi.org/10.1109/EuCNC/6GSummit58263.2023.10188245","url":null,"abstract":"The rapid expansion of 5G networks, coupled with the emergence of 6G technology, has highlighted the critical need for robust security measures to protect communication infrastructures. A primary security concern in 5G core networks is Distributed Denial of Service (DDoS) attacks, which target the GTP protocol. Conventional methods for detecting these attacks exhibit weaknesses and may struggle to effectively identify novel and undiscovered attacks. In this paper, we proposed a federated learning-based approach to detect DDoS attacks on the GTP protocol within a 5G core network. The suggested model leverages the collective intelligence of multiple devices to efficiently and privately identify DDoS attacks. Additionally, we have developed a 5G testbed architecture that simulates a sophisticated public network, making it ideal for evaluating AI-based security applications and testing the implementation and deployment of the proposed model. The results of our experiments demonstrate that the proposed unsupervised federated learning model effectively detects DDoS attacks on the 5G network while preserving the privacy of individual network data. This underscores the potential of federated learning in enhancing the security of 5G networks and beyond.","PeriodicalId":65870,"journal":{"name":"公共管理高层论坛","volume":"2016 1","pages":"442-447"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86433520","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 : 2023-06-06DOI: 10.1109/EuCNC/6GSummit58263.2023.10188299
C. Adjih, Chung Shue Chen, Chetanveer Sharma Gobin, Iman Hmedoush
This work aims to design protocol sequences through deep reinforcement learning (DRL). Protocol sequences are periodic binary sequences that define multiple access control among users, introduced for systems considering collision channel without feedback (CCw/oFB). In this paper, we leverage the recent advancement of DRL methods to design protocol sequences with desirable new properties, namely Throughput Maximizing User- Irrepressible (TMUI) sequences. TMUI has two specific properties: (i) user-irrepressibility (UI), and (ii) maximizing the minimum individual throughput among the users. We assumed that the transmission channel is divided into time slots and the starting time of each user in joining the system is arbitrary such that there exist random relative time offsets. We use a DRL approach to find TMUI sequences. We report the obtained TMUI protocol sequences and conduct numerical studies comparing TMUI against slotted ALOHA. Simulation results also show that the new medium access control (MAC) protocol does hold the UI property and can achieve substantially higher minimum individual user throughput, under the same system parameters.
{"title":"Designing Medium Access Control Protocol Sequences Through Deep Reinforcement Learning","authors":"C. Adjih, Chung Shue Chen, Chetanveer Sharma Gobin, Iman Hmedoush","doi":"10.1109/EuCNC/6GSummit58263.2023.10188299","DOIUrl":"https://doi.org/10.1109/EuCNC/6GSummit58263.2023.10188299","url":null,"abstract":"This work aims to design protocol sequences through deep reinforcement learning (DRL). Protocol sequences are periodic binary sequences that define multiple access control among users, introduced for systems considering collision channel without feedback (CCw/oFB). In this paper, we leverage the recent advancement of DRL methods to design protocol sequences with desirable new properties, namely Throughput Maximizing User- Irrepressible (TMUI) sequences. TMUI has two specific properties: (i) user-irrepressibility (UI), and (ii) maximizing the minimum individual throughput among the users. We assumed that the transmission channel is divided into time slots and the starting time of each user in joining the system is arbitrary such that there exist random relative time offsets. We use a DRL approach to find TMUI sequences. We report the obtained TMUI protocol sequences and conduct numerical studies comparing TMUI against slotted ALOHA. Simulation results also show that the new medium access control (MAC) protocol does hold the UI property and can achieve substantially higher minimum individual user throughput, under the same system parameters.","PeriodicalId":65870,"journal":{"name":"公共管理高层论坛","volume":"PP 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84321727","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 : 2023-06-06DOI: 10.1109/EuCNC/6GSummit58263.2023.10188278
Charbel Lahoud, Shahab Ehsanfar, K. Moessner
In this paper, we present a comprehensive evaluation of two prominent low-power wide-area networks (LPWAN) tech-nologies, low power long range alliance (LoRa) and narrow-band internet-of-things (NB-IoT), which are widely used in the internet-of-things (IoT) sector. We investigate their performance under challenging conditions, specifically in a scenario where the signal is subject to non-line-of-sight (NLOS) reception caused by signal diffraction. Additionally, we analyze the potential application challenges and use cases for each technology and provide insight into which technology is more suitable for specific scenarios. Our findings aim to inspire future researchers and manufacturers in the field of LPWAN and IoT.
{"title":"An Experimental Comparison of LoRa versus NB-IoT over Unlicensed Spectrum using Software Defined Radio","authors":"Charbel Lahoud, Shahab Ehsanfar, K. Moessner","doi":"10.1109/EuCNC/6GSummit58263.2023.10188278","DOIUrl":"https://doi.org/10.1109/EuCNC/6GSummit58263.2023.10188278","url":null,"abstract":"In this paper, we present a comprehensive evaluation of two prominent low-power wide-area networks (LPWAN) tech-nologies, low power long range alliance (LoRa) and narrow-band internet-of-things (NB-IoT), which are widely used in the internet-of-things (IoT) sector. We investigate their performance under challenging conditions, specifically in a scenario where the signal is subject to non-line-of-sight (NLOS) reception caused by signal diffraction. Additionally, we analyze the potential application challenges and use cases for each technology and provide insight into which technology is more suitable for specific scenarios. Our findings aim to inspire future researchers and manufacturers in the field of LPWAN and IoT.","PeriodicalId":65870,"journal":{"name":"公共管理高层论坛","volume":"1 1","pages":"652-657"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79921388","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 : 2023-06-06DOI: 10.1109/EuCNC/6GSummit58263.2023.10188248
Cara Watermann, Philipp Geuer, H. Wiemann, Roman Zhohov, Alexandros Palaios
As cellular networks evolve towards the 6th generation, new schemes are proposed in the area of Quality of Service (QoS) assurance. In recent years, predicting QoS gained some momentum as a way of satisfying specific connectivity requirements, supporting service assurance, and estimating the Quality of Experience (QoE). The QoS requirements to guarantee a certain QoE differ per use case, and hence depend on a multitude of factors, e.g., selecting an appropriate cell that can guarantee specific QoS requirements. Machine Learning (ML) is proposed as a method to improve network capabilities for QoE assurance by the use of predictive Quality of Service (pQoS). This in return can improve the offered QoS, reduce latency by selecting the most appropriate cell quickly, and improve the load-balancing at the network. The adoption of ML depends heavily on removing some of the roadblocks of applying ML in commercial networks. For example, ML-based algorithms are known to depend on a large amount of data, which might increase the usage of signaling and the battery consumption at the User Equipment (UE). We present an ML framework that can enable many of the aforementioned network capabilities, which does not require the introduction of new signaling types or proprietary data collection procedures. We showcase the benefits of the ML framework on an inter-frequency load balancing use case and discuss how ML can improve UE and network performance. Finally, we highlight the need to introduce the expected interference to the UE as an input feature for further improving QoS prediction performance. We test the performance of the prediction framework on data coming from a test network and evaluate the effects of e.g., different prediction thresholds.
{"title":"Towards a 3GPP Network-based Framework for Improving Service Assurance and Load Balancing","authors":"Cara Watermann, Philipp Geuer, H. Wiemann, Roman Zhohov, Alexandros Palaios","doi":"10.1109/EuCNC/6GSummit58263.2023.10188248","DOIUrl":"https://doi.org/10.1109/EuCNC/6GSummit58263.2023.10188248","url":null,"abstract":"As cellular networks evolve towards the 6th generation, new schemes are proposed in the area of Quality of Service (QoS) assurance. In recent years, predicting QoS gained some momentum as a way of satisfying specific connectivity requirements, supporting service assurance, and estimating the Quality of Experience (QoE). The QoS requirements to guarantee a certain QoE differ per use case, and hence depend on a multitude of factors, e.g., selecting an appropriate cell that can guarantee specific QoS requirements. Machine Learning (ML) is proposed as a method to improve network capabilities for QoE assurance by the use of predictive Quality of Service (pQoS). This in return can improve the offered QoS, reduce latency by selecting the most appropriate cell quickly, and improve the load-balancing at the network. The adoption of ML depends heavily on removing some of the roadblocks of applying ML in commercial networks. For example, ML-based algorithms are known to depend on a large amount of data, which might increase the usage of signaling and the battery consumption at the User Equipment (UE). We present an ML framework that can enable many of the aforementioned network capabilities, which does not require the introduction of new signaling types or proprietary data collection procedures. We showcase the benefits of the ML framework on an inter-frequency load balancing use case and discuss how ML can improve UE and network performance. Finally, we highlight the need to introduce the expected interference to the UE as an input feature for further improving QoS prediction performance. We test the performance of the prediction framework on data coming from a test network and evaluate the effects of e.g., different prediction thresholds.","PeriodicalId":65870,"journal":{"name":"公共管理高层论坛","volume":"282 1","pages":"430-435"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76808628","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 : 2023-06-06DOI: 10.1109/EuCNC/6GSummit58263.2023.10188333
H. Kokkinen, A. Piemontese, Arto Reis-Kivinen, Lukasz Kulacz, Nathan Borios, Carla Amatetti
Satellite communication systems are fundamental components to deploy the future smart and sustainable networks and to achieve the ambitious goal of bringing wireless connectivity anywhere, anytime, at any device. In this new role, one of the main challenges that satellite communication component has to face is the maximization of the spectrum usage. 3GPP communication technologies are extended from Terrestrial Networks (TNs) to Non-Terrestrial Networks (NTNs), but so far the standardisation efforts have been focused on systems where TNs and NTNs operate in their dedicated frequency bands. In this paper, a dynamic spectrum sharing model between NTN elements, in a Non Geostationary orbit, and TN is proposed. A Proof of Concept (PoC) is developed, in order to carry out the interference protection computation. We show that the developed spectrum sharing model can enable spectrum sharing between NTN and TN when their coverage areas do not have to overlap, that the sharing arrangement increases significantly the service coverage in the frequency band and slightly improves the spectrum utilization efficiency. It is also shown that the spectrum management system is able to manage the interference level and to keep the interference-to-noise ratio at the TN user equipment below the specified limit. In fact, the aggregate interference caused by the sharing arrangement does not decrease the capacity of the TN downlink.
{"title":"Proof of Concept for Spectrum Sharing between Terrestrial and Satellite Networks","authors":"H. Kokkinen, A. Piemontese, Arto Reis-Kivinen, Lukasz Kulacz, Nathan Borios, Carla Amatetti","doi":"10.1109/EuCNC/6GSummit58263.2023.10188333","DOIUrl":"https://doi.org/10.1109/EuCNC/6GSummit58263.2023.10188333","url":null,"abstract":"Satellite communication systems are fundamental components to deploy the future smart and sustainable networks and to achieve the ambitious goal of bringing wireless connectivity anywhere, anytime, at any device. In this new role, one of the main challenges that satellite communication component has to face is the maximization of the spectrum usage. 3GPP communication technologies are extended from Terrestrial Networks (TNs) to Non-Terrestrial Networks (NTNs), but so far the standardisation efforts have been focused on systems where TNs and NTNs operate in their dedicated frequency bands. In this paper, a dynamic spectrum sharing model between NTN elements, in a Non Geostationary orbit, and TN is proposed. A Proof of Concept (PoC) is developed, in order to carry out the interference protection computation. We show that the developed spectrum sharing model can enable spectrum sharing between NTN and TN when their coverage areas do not have to overlap, that the sharing arrangement increases significantly the service coverage in the frequency band and slightly improves the spectrum utilization efficiency. It is also shown that the spectrum management system is able to manage the interference level and to keep the interference-to-noise ratio at the TN user equipment below the specified limit. In fact, the aggregate interference caused by the sharing arrangement does not decrease the capacity of the TN downlink.","PeriodicalId":65870,"journal":{"name":"公共管理高层论坛","volume":"72 1","pages":"276-281"},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87807801","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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