With the emerging commercial deployments of 5G Network, the Mobile Network Operators (MNOs) will be able to offer more significant network capabilities such as efficient ultra-reliable and low latency communications (URLLC), higher bandwidth for data transfer with enhanced Mobile Broadband (eMBB), and massive capacity to connect devices with massive Internet of Things (mIoT). MNOs are making huge investments to setup 5G Networks with an anticipation of growth in their revenues. However, MNOs may not see the return of investment through end user consumer base alone and may need additional revenue streams. Thus, 5G system has been designed to have advanced built-in features such as network slicing and edge computing, considering requirements from enterprise segments or vertical industries including healthcare, automotive, smart factories, mission critical communications, etc. To enable more rapid deployment of vertical services, the 5G deployments require fostering innovation at the application layer. With the growing needs of verticals industries, the operators are now focusing on enabling standards for vertical applications in 3rd Generation Partnership Project (3GPP), a global standards forum for 5G. In this paper, the authors explain the Service Enabler Architecture Layer (SEAL) standard for 5G verticals and the services offered by the enabler layer. The paper also elaborates how the operators can leverage the SEAL to quickly develop and deploy vertical applications over the 5G Network.
{"title":"Service Enabler Layer for 5G Verticals","authors":"Sapan Shah, B. Pattan, Nishant Gupta, Narendranath Durga Tangudu, Suresh Chitturi","doi":"10.1109/5GWF49715.2020.9221425","DOIUrl":"https://doi.org/10.1109/5GWF49715.2020.9221425","url":null,"abstract":"With the emerging commercial deployments of 5G Network, the Mobile Network Operators (MNOs) will be able to offer more significant network capabilities such as efficient ultra-reliable and low latency communications (URLLC), higher bandwidth for data transfer with enhanced Mobile Broadband (eMBB), and massive capacity to connect devices with massive Internet of Things (mIoT). MNOs are making huge investments to setup 5G Networks with an anticipation of growth in their revenues. However, MNOs may not see the return of investment through end user consumer base alone and may need additional revenue streams. Thus, 5G system has been designed to have advanced built-in features such as network slicing and edge computing, considering requirements from enterprise segments or vertical industries including healthcare, automotive, smart factories, mission critical communications, etc. To enable more rapid deployment of vertical services, the 5G deployments require fostering innovation at the application layer. With the growing needs of verticals industries, the operators are now focusing on enabling standards for vertical applications in 3rd Generation Partnership Project (3GPP), a global standards forum for 5G. In this paper, the authors explain the Service Enabler Architecture Layer (SEAL) standard for 5G verticals and the services offered by the enabler layer. The paper also elaborates how the operators can leverage the SEAL to quickly develop and deploy vertical applications over the 5G Network.","PeriodicalId":232687,"journal":{"name":"2020 IEEE 3rd 5G World Forum (5GWF)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127412190","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 : 2020-09-01DOI: 10.1109/5GWF49715.2020.9221243
V. K. Shrivastava, Rohan Raj, Lalit Pathak
The exponential growth of mobile social networks (MSN) catering popular social networking services accompanied with rapid proliferation of smart-phones is bringing a paradigm shift for mobile communication. Service access on these MSNs is mostly asynchronous resulting in unpredictable traffic patterns. Present mobile networks are inherently deficient in catering to these new requirements and suffer from congestion at the network core and the radio access network (RAN), poor utilization of communication resources, low quality of experience for users. Previous works in Literature have provided generic framework for service delivery for MSN, however, they lack in addressing the dynamic scenarios of user mobility and meeting varied quality of service (QoS) requirements imposed by different social networking services. In this paper, we target enhancing the performance for MSN. Particularly, we investigate and exploit the composite multi-content nature of social network services and leverage the combined potential of broadcast and unicast in suitably disseminating contents/sub-contents. Further, we provide an in depth analysis of user mobility and service QoS factors and their efficient handling during cache building and allocation steps for MSN. Multihop communication is considered to better facilitate the proximal device to device link data exchange capitalizing on transferred contents, and its impact over the incurred RAN cost is examined. We show, with simulation results, a substantial saving for RAN cost is achieved with considering these new factors.
{"title":"A Novel Caching Framework for Mobile Social Networks in 5G and Beyond","authors":"V. K. Shrivastava, Rohan Raj, Lalit Pathak","doi":"10.1109/5GWF49715.2020.9221243","DOIUrl":"https://doi.org/10.1109/5GWF49715.2020.9221243","url":null,"abstract":"The exponential growth of mobile social networks (MSN) catering popular social networking services accompanied with rapid proliferation of smart-phones is bringing a paradigm shift for mobile communication. Service access on these MSNs is mostly asynchronous resulting in unpredictable traffic patterns. Present mobile networks are inherently deficient in catering to these new requirements and suffer from congestion at the network core and the radio access network (RAN), poor utilization of communication resources, low quality of experience for users. Previous works in Literature have provided generic framework for service delivery for MSN, however, they lack in addressing the dynamic scenarios of user mobility and meeting varied quality of service (QoS) requirements imposed by different social networking services. In this paper, we target enhancing the performance for MSN. Particularly, we investigate and exploit the composite multi-content nature of social network services and leverage the combined potential of broadcast and unicast in suitably disseminating contents/sub-contents. Further, we provide an in depth analysis of user mobility and service QoS factors and their efficient handling during cache building and allocation steps for MSN. Multihop communication is considered to better facilitate the proximal device to device link data exchange capitalizing on transferred contents, and its impact over the incurred RAN cost is examined. We show, with simulation results, a substantial saving for RAN cost is achieved with considering these new factors.","PeriodicalId":232687,"journal":{"name":"2020 IEEE 3rd 5G World Forum (5GWF)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129564774","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 : 2020-09-01DOI: 10.1109/5GWF49715.2020.9221405
M. Singh, Shwetha Vittal, A. Franklin
5G is designed to meet the requirements of various network services such as eMBB (enhanced Mobile Broadband), URLLC (Ultra Reliable Low Latency Communications), and mMTC (massive Machine Type Communication) by making use of the technologies such as Software Defined Networking (SDN) and Network Function Virtualization (NFV). These services can be provided through isolated virtual networks bringing in the concept of network slicing in 5G which helps in adjusting the resources dynamically which in turn can maximize resource utilization across the services. The dynamic adjustment of resources can be achieved by monitoring slice instances in the Closed Loop Automation (CLA) to make quick decisions on slice scaling, selection, etc. In this paper, we propose a Self Regulating Network Slicing (SERENS) framework for slice monitoring and selection in 5G. We have developed a prototype of the proposed SERENS framework in a 5G test-bed system and shown that proper slice selection can avoid wastage of resources of slices by up to 60%. The proposed slice selection algorithm will help the operator to serve a higher number of users while making the efficient usage of the available resources.
{"title":"SERENS: Self Regulating Network Slicing in 5G for Efficient Resource Utilization","authors":"M. Singh, Shwetha Vittal, A. Franklin","doi":"10.1109/5GWF49715.2020.9221405","DOIUrl":"https://doi.org/10.1109/5GWF49715.2020.9221405","url":null,"abstract":"5G is designed to meet the requirements of various network services such as eMBB (enhanced Mobile Broadband), URLLC (Ultra Reliable Low Latency Communications), and mMTC (massive Machine Type Communication) by making use of the technologies such as Software Defined Networking (SDN) and Network Function Virtualization (NFV). These services can be provided through isolated virtual networks bringing in the concept of network slicing in 5G which helps in adjusting the resources dynamically which in turn can maximize resource utilization across the services. The dynamic adjustment of resources can be achieved by monitoring slice instances in the Closed Loop Automation (CLA) to make quick decisions on slice scaling, selection, etc. In this paper, we propose a Self Regulating Network Slicing (SERENS) framework for slice monitoring and selection in 5G. We have developed a prototype of the proposed SERENS framework in a 5G test-bed system and shown that proper slice selection can avoid wastage of resources of slices by up to 60%. The proposed slice selection algorithm will help the operator to serve a higher number of users while making the efficient usage of the available resources.","PeriodicalId":232687,"journal":{"name":"2020 IEEE 3rd 5G World Forum (5GWF)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122858460","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 : 2020-09-01DOI: 10.1109/5GWF49715.2020.9221389
Aditya Singh Sengar, R. Gangopadhyay, Soumitra Debnath
Incorporation of Device-to-Device communication increases the capacity of a wireless network while simultaneously reducing its reliance on the core network, which makes D2D one of the most important enabling technology for 5G and beyond wireless systems. However, these gains in network performance are achieved alongside a considerable increase in interference. Hence, interference modelling is of prime importance.In this work, statistical analysis and modelling of the aggregate interference generated by an underlay D2D network has been done by Gaussian Mixture Models along with statistical validation through two-sample Kolmogorov-Smirnov test. The generated models are utilized for channel allocation and provide significant capacity improvement for a D2D link.The results and analysis presented in this paper provide novel insights upon an interference-resistant D2D network design.
{"title":"Interference Modelling for an Underlay D2D Network for Efficient Resource Allocation","authors":"Aditya Singh Sengar, R. Gangopadhyay, Soumitra Debnath","doi":"10.1109/5GWF49715.2020.9221389","DOIUrl":"https://doi.org/10.1109/5GWF49715.2020.9221389","url":null,"abstract":"Incorporation of Device-to-Device communication increases the capacity of a wireless network while simultaneously reducing its reliance on the core network, which makes D2D one of the most important enabling technology for 5G and beyond wireless systems. However, these gains in network performance are achieved alongside a considerable increase in interference. Hence, interference modelling is of prime importance.In this work, statistical analysis and modelling of the aggregate interference generated by an underlay D2D network has been done by Gaussian Mixture Models along with statistical validation through two-sample Kolmogorov-Smirnov test. The generated models are utilized for channel allocation and provide significant capacity improvement for a D2D link.The results and analysis presented in this paper provide novel insights upon an interference-resistant D2D network design.","PeriodicalId":232687,"journal":{"name":"2020 IEEE 3rd 5G World Forum (5GWF)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128496892","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 : 2020-09-01DOI: 10.1109/5GWF49715.2020.9221410
Vikash Mishra, D. Das, Namo Narayan Singh
Ultra-reliable low latency communication (URLLC) is a key feature in 5G which requires improved mobility performance and reliability. In future, the number of devices are going to increase many times in 5G compared to current 4G, so the number of mobility (handover) scenarios are bound to increase many folds, and without proper technologies it may induce more handover failures. According to tests done in North America it is observed that handover failure (HOF) rate is 7.6% in urban areas and 21.7% in downtown area while successful recovery from HOF is only 38% [9]. Also, it is observed that if user equipment (UE) faces radio link failure (RLF) which leads to HOF, then the service interruption time is more. Therefore, to ensure better quality of experience (QoE) in 5G NR (New Radio), it is important to have minimal interruption time, and high handover success rate. In this paper we propose a novel Machine Learning (ML) and beam measurement based advance handover (HO) algorithm. In this concept, HO is initiated in advance before UE runs into RLF to ensure less HOF. In our proposed algorithm, the Network parameters used to train the ML model is based on serving cell reference signal received power (RSRP), block error rate (BLER), Timing Advance (TA) and serving beam direction. The proposed idea performance with existing Handover mechanism shows reduction of HOF rate by 35%.
超可靠低延迟通信(URLLC)是5G的关键特性，需要提高移动性能和可靠性。未来5G的设备数量会比现在的4G增加很多倍，所以移动性(切换)场景的数量必然会增加很多倍，如果没有合适的技术，可能会导致更多的切换失败。根据北美地区的测试，市区切换失败率为7.6%，市区切换失败率为21.7%，而成功恢复HOF的比例仅为38%[9]。此外，如果用户设备(UE)面临无线电链路故障(RLF)导致HOF，则业务中断时间更长。因此，为了确保5G NR (New Radio)中更好的体验质量(QoE)，重要的是要尽量减少中断时间，并提高切换成功率。本文提出了一种基于机器学习和波束测量的超前切换算法。在这个概念中，在UE进入RLF之前，提前启动HO，以确保较少的HOF。在我们提出的算法中，用于训练ML模型的网络参数是基于服务小区参考信号接收功率(RSRP)、分组错误率(BLER)、时序推进(TA)和服务波束方向。在现有的切换机制下，所提出的思想性能降低了35%的HOF率。
{"title":"Novel Algorithm to Reduce Handover Failure Rate in 5G Networks","authors":"Vikash Mishra, D. Das, Namo Narayan Singh","doi":"10.1109/5GWF49715.2020.9221410","DOIUrl":"https://doi.org/10.1109/5GWF49715.2020.9221410","url":null,"abstract":"Ultra-reliable low latency communication (URLLC) is a key feature in 5G which requires improved mobility performance and reliability. In future, the number of devices are going to increase many times in 5G compared to current 4G, so the number of mobility (handover) scenarios are bound to increase many folds, and without proper technologies it may induce more handover failures. According to tests done in North America it is observed that handover failure (HOF) rate is 7.6% in urban areas and 21.7% in downtown area while successful recovery from HOF is only 38% [9]. Also, it is observed that if user equipment (UE) faces radio link failure (RLF) which leads to HOF, then the service interruption time is more. Therefore, to ensure better quality of experience (QoE) in 5G NR (New Radio), it is important to have minimal interruption time, and high handover success rate. In this paper we propose a novel Machine Learning (ML) and beam measurement based advance handover (HO) algorithm. In this concept, HO is initiated in advance before UE runs into RLF to ensure less HOF. In our proposed algorithm, the Network parameters used to train the ML model is based on serving cell reference signal received power (RSRP), block error rate (BLER), Timing Advance (TA) and serving beam direction. The proposed idea performance with existing Handover mechanism shows reduction of HOF rate by 35%.","PeriodicalId":232687,"journal":{"name":"2020 IEEE 3rd 5G World Forum (5GWF)","volume":"166 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122656601","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 : 2020-09-01DOI: 10.1109/5GWF49715.2020.9221278
Seokjae Moon, Jang-Won Lee
In this paper, we develop a repetition-based grant-free scheme, called DMRS-Applied Repetition Transmission (DART), to support mMTC user equipments (UEs). In DART, the demodulation reference signals (DMRSs) are exploited to estimate the channels as well as to implicitly inform the repetition patterns to the gNB. Based on the detected DMRSs, the gNB performs successive interference cancellation (SIC) to further decode the data of mMTC UEs that transmit their data on the same resource block. DART achieves high success rate, low latency, and low SIC overhead by adopting DMRS-based SIC ordering. Simulation results show that DART is able to support mMTC UEs effectively.
{"title":"DMRS-Applied Repetition Transmission (DART): Grant-Free Scheme for mMTC","authors":"Seokjae Moon, Jang-Won Lee","doi":"10.1109/5GWF49715.2020.9221278","DOIUrl":"https://doi.org/10.1109/5GWF49715.2020.9221278","url":null,"abstract":"In this paper, we develop a repetition-based grant-free scheme, called DMRS-Applied Repetition Transmission (DART), to support mMTC user equipments (UEs). In DART, the demodulation reference signals (DMRSs) are exploited to estimate the channels as well as to implicitly inform the repetition patterns to the gNB. Based on the detected DMRSs, the gNB performs successive interference cancellation (SIC) to further decode the data of mMTC UEs that transmit their data on the same resource block. DART achieves high success rate, low latency, and low SIC overhead by adopting DMRS-based SIC ordering. Simulation results show that DART is able to support mMTC UEs effectively.","PeriodicalId":232687,"journal":{"name":"2020 IEEE 3rd 5G World Forum (5GWF)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130187169","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 : 2020-09-01DOI: 10.1109/5GWF49715.2020.9221290
Roja Vadlamudi, D. S. Kumar
In this paper, we propose the exploration of the Triple-Band DP (Dual Polarized), Low Profile and High Gain MIMO Antenna for 4G/5G BTS Applications. The design consists of 4 tapered dual polarized bow-tie slot radiators that are fed by pairs of coaxial cables with metallic cylindrical post for mechanical support. The radiating elements are operating at 2.5GHz, 3.5GHz and 6.0GHz. In terms of fundamental radiation characteristics, the 4/5G slot radiators provide dualpolarization characteristic with similar performances. A pair of slotted 4/5G template is created across each radiator in order to improve the isolation characteristic between the adjacent arms with feeding ports of the dual polarized radiators. The pattern of unidirectional radiation is generated by placing a metal ground plane at a distance of λ0/4.The radiating components are equipped for service at 3GPP LTE band 40(2.3-2.4GHz), band 41 (2.496-2.690GHz), band 42 (3.4-3.6GHz) and 6.0-6.13GHz with VSWR<1.5 in the above bands. The proposed MIMO antenna provides very high gain radiation patterns with strong S-parameters. With this feature proposed antenna has a potential application for use in the future 5G systems.
{"title":"Triple-Band DP, Low Profile and High Gain Antenna with High Isolation for 4G (Band 40/41) and 5G BTS Applications","authors":"Roja Vadlamudi, D. S. Kumar","doi":"10.1109/5GWF49715.2020.9221290","DOIUrl":"https://doi.org/10.1109/5GWF49715.2020.9221290","url":null,"abstract":"In this paper, we propose the exploration of the Triple-Band DP (Dual Polarized), Low Profile and High Gain MIMO Antenna for 4G/5G BTS Applications. The design consists of 4 tapered dual polarized bow-tie slot radiators that are fed by pairs of coaxial cables with metallic cylindrical post for mechanical support. The radiating elements are operating at 2.5GHz, 3.5GHz and 6.0GHz. In terms of fundamental radiation characteristics, the 4/5G slot radiators provide dualpolarization characteristic with similar performances. A pair of slotted 4/5G template is created across each radiator in order to improve the isolation characteristic between the adjacent arms with feeding ports of the dual polarized radiators. The pattern of unidirectional radiation is generated by placing a metal ground plane at a distance of λ0/4.The radiating components are equipped for service at 3GPP LTE band 40(2.3-2.4GHz), band 41 (2.496-2.690GHz), band 42 (3.4-3.6GHz) and 6.0-6.13GHz with VSWR<1.5 in the above bands. The proposed MIMO antenna provides very high gain radiation patterns with strong S-parameters. With this feature proposed antenna has a potential application for use in the future 5G systems.","PeriodicalId":232687,"journal":{"name":"2020 IEEE 3rd 5G World Forum (5GWF)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130039646","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 : 2020-09-01DOI: 10.1109/5GWF49715.2020.9221152
Suresh C. Gupta, G. Gupta, H. Saran
Today’s routing infrastructure uses BGP for interdomain routing, which suffers from several well-known issues - slow convergence, lack of transparency, limited control in routing, and limited scalability for handling the massive IPv6 address space. As a result, it cannot meet the stringent requirements 5G ultra-reliable low-latency communication (URLLC), which has been designed for latency-critical real-time applications such as tele robotics and augmented reality, and must scale up to support millions of IoT devices. To address these shortcomings of today’s routing infrastructure, we propose a four layer hierarchical network architecture, that associates a real (geographical) address with each IP address. The real address has four parts - country, state, district, and AS - that correspond to the four layers of routing hierarchy, and is used for inter-domain routing; the IP address is used for routing only within an AS. The hierarchical routing using geographical addresses enables quick convergence, fewer number of routing hops, and a very small number of forwarding rules in each router. Each network layer can further be sliced for the three broad categories of 5G users i.e mBBC, MTC and uRLLC. As deploying a new architecture across the globe is challenging, we discuss how it can be incrementally deployed one country at a time, exploiting existing infrastructure for international routing.
{"title":"New Vision for 5G Backbone Network Architecture","authors":"Suresh C. Gupta, G. Gupta, H. Saran","doi":"10.1109/5GWF49715.2020.9221152","DOIUrl":"https://doi.org/10.1109/5GWF49715.2020.9221152","url":null,"abstract":"Today’s routing infrastructure uses BGP for interdomain routing, which suffers from several well-known issues - slow convergence, lack of transparency, limited control in routing, and limited scalability for handling the massive IPv6 address space. As a result, it cannot meet the stringent requirements 5G ultra-reliable low-latency communication (URLLC), which has been designed for latency-critical real-time applications such as tele robotics and augmented reality, and must scale up to support millions of IoT devices. To address these shortcomings of today’s routing infrastructure, we propose a four layer hierarchical network architecture, that associates a real (geographical) address with each IP address. The real address has four parts - country, state, district, and AS - that correspond to the four layers of routing hierarchy, and is used for inter-domain routing; the IP address is used for routing only within an AS. The hierarchical routing using geographical addresses enables quick convergence, fewer number of routing hops, and a very small number of forwarding rules in each router. Each network layer can further be sliced for the three broad categories of 5G users i.e mBBC, MTC and uRLLC. As deploying a new architecture across the globe is challenging, we discuss how it can be incrementally deployed one country at a time, exploiting existing infrastructure for international routing.","PeriodicalId":232687,"journal":{"name":"2020 IEEE 3rd 5G World Forum (5GWF)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115780045","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 : 2020-09-01DOI: 10.1109/5GWF49715.2020.9221100
Ahmad Zaza, Suleiman K. Kharroub, K. Abualsaud
Internet of Things (IoT) is becoming more frequently used in more applications as the number of connected devices is in a rapid increase. More connected devices result in bigger challenges in terms of scalability, maintainability and most importantly security especially when it comes to 5G networks. The security aspect of IoT devices is an infant field, which is why it is our focus in this paper. Multiple IoT device manufacturers do not consider securing the devices they produce for different reasons like cost reduction or to avoid using energy-harvesting components. Such potentially malicious devices might be exploited by the adversary to do multiple harmful attacks. Therefore, we developed a system that can recognize malicious behavior of a specific IoT node on the network. Through convolutional neural network and monitoring, we were able to provide malware detection for IoT using a central node that can be installed within the network. The achievement shows how such models can be generalized and applied easily to any network while clearing out any stigma regarding deep learning techniques.
{"title":"Lightweight IoT Malware Detection Solution Using CNN Classification","authors":"Ahmad Zaza, Suleiman K. Kharroub, K. Abualsaud","doi":"10.1109/5GWF49715.2020.9221100","DOIUrl":"https://doi.org/10.1109/5GWF49715.2020.9221100","url":null,"abstract":"Internet of Things (IoT) is becoming more frequently used in more applications as the number of connected devices is in a rapid increase. More connected devices result in bigger challenges in terms of scalability, maintainability and most importantly security especially when it comes to 5G networks. The security aspect of IoT devices is an infant field, which is why it is our focus in this paper. Multiple IoT device manufacturers do not consider securing the devices they produce for different reasons like cost reduction or to avoid using energy-harvesting components. Such potentially malicious devices might be exploited by the adversary to do multiple harmful attacks. Therefore, we developed a system that can recognize malicious behavior of a specific IoT node on the network. Through convolutional neural network and monitoring, we were able to provide malware detection for IoT using a central node that can be installed within the network. The achievement shows how such models can be generalized and applied easily to any network while clearing out any stigma regarding deep learning techniques.","PeriodicalId":232687,"journal":{"name":"2020 IEEE 3rd 5G World Forum (5GWF)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126480576","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 : 2020-09-01DOI: 10.1109/5GWF49715.2020.9221097
Sarthak Sunil Dhanke, S. Sharma, Alok Kumar, Manish Mandloi
In this paper, we propose a downlink index modulation multiple access (IM-MA) system using deep learning (DL) based detection. In the proposed IM-MA, a user transmits information by modulating either active antenna indexes or signal constellation points, unlike the conventional IM-MA, where each user sends information using both the antenna indexes and constellation points. Therefore, the proposed IM-MA can accommodate more users in a network. Further, we use the DL-based detector via deep neural network (DNN) models, for each user’s symbol detection to improve the proposed IM-MA system’s performance. The received signal is preprocessed by considering the system’s apriory knowledge before going into the DNNs. DNN models are trained offline via simulated data and then applied for online symbol detection. Simulation results show the effectiveness of DNN detectors in terms of symbol error rate performance over Rayleigh fading channels with a lower runtime and complexity as compared to optimal maximum-likelihood detection.
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