Design of an Interconnection Architecture and Sizing of Two (2) EPC Core Networks: The Case of Orange-Guinea

With the arrival of the 4G and 5G,the telecommunications networks have experienced a large expansion of these networks.That enabled the integration of many services and adequate flow,thus enabling the operators to respond to the growing demand of users.This rapid evolution has given the operators to adapt,their methods to the new technologies that increase.This complexity becomes more important,when these networks include several technologies to access different from the heterogeneous network like in the 4G network.The dimensional new challenges tell the application and the considerable increase in demand for services and the compatibility with existing networks,the management of mobility intercellular of users and it offers a better quality of services.Thus,the proposed solution to meet these new requirements is the sizing of the EPC(Evolved Packet Core)core network to support the 5G access network.For the case of Orange Guinea,this involves setting up an architecture for interconnecting the core networks of Sonfonia and Camayenne.The objectives of our work are of two orders:(1)to propose these solutions and recommendations for the heart network EPC sizing and the deployment to be adopted;(2)supply and architectural interconnection in the heart network EPC and an existing heart network.In our work,the model of traffic in communication that we use to calculate the traffic generated with each technology has link in the network of the heart.

Flex Ethernet Technology and Application in 5G Mobile Transport Network

With the advent of 5G era,the rise of cloud services,virtual reality/virtual reality(AR/VR),vehicle networking and other technologies has put forward new requirements for the bandwidth and delay of the bearer network.Traditional Ethernet technology cannot meet the new requirements very well.Flex Ethernet(FlexE)technology has emerged as the times require.This paper introduces the background,standardization process,functional principle,application mode and technical advantages of FlexE technology,and finally analyses its application prospects and shortcomings in 5G mobile transport network.

Network-Aided Intelligent Traffic Steering in 5G Mobile Networks

Recently,the fifth generation(5G)of mobile networks has been deployed and various ranges of mobile services have been provided.The 5G mobile network supports improved mobile broadband,ultra-low latency and densely deployed massive devices.It allows multiple radio access technologies and interworks them for services.5G mobile systems employ traffic steering techniques to efficiently use multiple radio access technologies.However,conventional traffic steering techniques do not consider dynamic network conditions efficiently.In this paper,we propose a network aided traffic steering technique in 5G mobile network architecture.5G mobile systems monitor network conditions and learn with network data.Through a machine learning algorithm such as a feed-forward neural network,it recognizes dynamic network conditions and then performs traffic steering.The proposed scheme controls traffic for multiple radio access according to the ratio of measured throughput.Thus,it can be expected to improve traffic steering efficiency.The performance of the proposed traffic steering scheme is evaluated using extensive computer simulations.

A Review in the Core Technologies of 5G: Device-to-Device Communication, Multi-Access Edge Computing and Network Function Virtualization

5G is a new generation of mobile networking that aims to achieve unparalleled speed and performance. To accomplish this, three technologies, Device-to-Device communication (D2D), multi-access edge computing (MEC) and network function virtualization (NFV) with ClickOS, have been a significant part of 5G, and this paper mainly discusses them. D2D enables direct communication between devices without the relay of base station. In 5G, a two-tier cellular network composed of traditional cellular network system and D2D is an efficient method for realizing high-speed communication. MEC unloads work from end devices and clouds platforms to widespread nodes, and connects the nodes together with outside devices and third-party providers, in order to diminish the overloading effect on any device caused by enormous applications and improve users’ quality of experience (QoE). There is also a NFV method in order to fulfill the 5G requirements. In this part, an optimized virtual machine for middle-boxes named ClickOS is introduced, and it is evaluated in several aspects. Some middle boxes are being implemented in the ClickOS and proved to have outstanding performances.

TCP-LTE/5G Cross-layer performance analysis tool for high mobility data networking and a case study on high-speed railway

Nowadays,high mobility scenarios have become increasingly common.The widespread adoption of High-speed Rail(HSR)in China exemplifies this trend,while more promising use cases,such as vehicle-to-everything,continue to emerge.However,the Internet access provided in high mobility environments stllstruggles to achieve seamless connectivity.The next generation of wireless cellular technology 5 G further poses more requirements on the endto-end evolution to fully utilize its ultra-high band-width,while existing network diagnostic tools focus on above-IP layers or below-IP layers only.We then propose HiMoDiag,which enables flexible online analysis of the network performance in a cross-layer manner,i.e.,from the top(application layer)to the bottom(physical layer).We believe HiMoDiag could greatly simplify the process of pinpointing the deficiencies of the Internet access delivery on HSR,lead to more timely optimization and ultimately help to improve the network performance.

Review of the Development of China's Mobile Broadband Networks

The year of 2014 saw the beginning of China's LTE,which marks that China has become one of the major engines for the global LTE development.China dazzled in the construction of LTE networks,subscribers,and industry chain.However,the policy formulated around TD-LTE also put China in predicament and brought it many challenges.With this article,we are going to put China's market for mobile broadband networks into perspective,focusing on the development of China's LTE market,challenges that encountered,and the research in this area in the years to come.Besides,in regards to the problems that already appeared,we will,from policy-making,industry-level,and technological points of view,offer our suggestions on how China should do to make this market robust.

SDN-Based Data Offloading for 5G Mobile Networks

The rapid growth of 3G/4G enabled devices such as smartphones and tablets in large numbers has created increased demand for mobile data services. Wi-Fi offloading helps satisfy the requirements of data-rich applications and terminals with improved multi- media. Wi-Fi is an essential approach to alleviating mobile data traffic load on a cellular network because it provides extra capacity and improves overall performance. In this paper, we propose an integrated LTE/Wi-Fi architecture with software-defined networking （SDN） abstraction in mobile baekhaul and enhanced components that facilitate the move towards next-generation 5G mo- bile networks. Our proposed architecture enables programmable offloading policies that take into account real-time network conditions as well as the status of devices and applications. This mechanism improves overall network performance by deriving real- time policies and steering traffic between cellular and Wi-Fi networks more efficiently.

Adaptive Resource Allocation Algorithm for 5G Vehicular Cloud Communication

The current resource allocation in 5G vehicular networks for mobile cloud communication faces several challenges,such as low user utilization,unbalanced resource allocation,and extended adaptive allocation time.We propose an adaptive allocation algorithm for mobile cloud communication resources in 5G vehicular networks to address these issues.This study analyzes the components of the 5G vehicular network architecture to determine the performance of different components.It is ascertained that the communication modes in 5G vehicular networks for mobile cloud communication include in-band and out-of-band modes.Furthermore,this study analyzes the single-hop and multi-hop modes in mobile cloud communication and calculates the resource transmission rate and bandwidth in different communication modes.The study also determines the scenario of one-way and two-way vehicle lane cloud communication network connectivity,calculates the probability of vehicle network connectivity under different mobile cloud communication radii,and determines the amount of cloud communication resources required by vehicles in different lane scenarios.Based on the communication status of users in 5G vehicular networks,this study calculates the bandwidth and transmission rate of the allocated channels using Shannon’s formula.It determines the adaptive allocation of cloud communication resources,introduces an objective function to obtain the optimal solution after allocation,and completes the adaptive allocation process.The experimental results demonstrate that,with the application of the proposed method,the maximum utilization of user communication resources reaches approximately 99%.The balance coefficient curve approaches 1,and the allocation time remains under 2 s.This indicates that the proposed method has higher adaptive allocation efficiency.

Mobile Edge Computing Towards 5G: Vision, Recent Progress, and Open Challenges

Mobile Edge Computing(MEC) is an emerging technology in 5G era which enables the provision of the cloud and IT services within the close proximity of mobile subscribers.It allows the availability of the cloud servers inside or adjacent to the base station.The endto-end latency perceived by the mobile user is therefore reduced with the MEC platform.The context-aware services are able to be served by the application developers by leveraging the real time radio access network information from MEC.The MEC additionally enables the compute intensive applications execution in the resource constraint devices with the collaborative computing involving the cloud servers.This paper presents the architectural description of the MEC platform as well as the key functionalities enabling the above features.The relevant state-of-the-art research efforts are then surveyed.The paper finally discusses and identifies the open research challenges of MEC.

Mobile Edge Computing and Field Trial Results for 5G Low Latency Scenario

Through enabling the IT and cloud computation capacities at Radio Access Network(RAN),Mobile Edge Computing(MEC) makes it possible to deploy and provide services locally.Therefore,MEC becomes the potential technology to satisfy the requirements of 5G network to a certain extent,due to its functions of services localization,local breakout,caching,computation offloading,network context information exposure,etc.Especially,MEC can decrease the end-to-end latency dramatically through service localization and caching,which is key requirement of 5G low latency scenario.However,the performance of MEC still needs to be evaluated and verified for future deployment.Thus,the concept of MEC is introduced into5 G architecture and analyzed for different 5G scenarios in this paper.Secondly,the evaluation of MEC performance is conducted and analyzed in detail,especially for network end-to-end latency.In addition,some challenges of the MEC are also discussed for future deployment.

Conflict Resolution Strategy in Handover Management for 4G and 5G Networks

Fifth-generation(5G)cellular networks offer high transmission rates in dense urban environments.However,a massive deployment of small cells will be required to provide wide-area coverage,which leads to an increase in the number of handovers(HOs).Mobility management is an important issue that requires considerable attention in heterogeneous networks,where 5G ultra-dense small cells coexist with current fourth-generation(4G)networks.Although mobility robustness optimization(MRO)and load balancing optimization(LBO)functions have been introduced in the 3GPP standard to address HO problems,non-robust and nonoptimal algorithms for selecting appropriate HO control parameters(HCPs)still exist,and an optimal solution is subjected to compromise between LBO and MRO functions.Thus,HO decision algorithms become inefficient.This paper proposes a conflict resolution technique to address the contradiction between MRO and LBO functions.The proposed technique exploits received signal reference power(RSRP),cell load and user speed to adapt HO margin(HM)and time to trigger(TTT).Estimated HM and TTT depend on a weighting function and HO type which is represented by user status during mobility.The proposed technique is validated with other existing algorithms from the literature.Simulation results demonstrate that the proposed technique outperforms existing algorithms overall performance metrics.The proposed technique reduces the overall average HO ping-pong probability,HO failure rate and interruption time by more than 90%,46%and 58%,respectively,compared with the other schemes overall speed scenarios and simulation time.

Reinforcement Learning-Based Optimization for Drone Mobility in 5G and Beyond Ultra-Dense Networks

Drone applications in 5th generation(5G)networks mainly focus on services and use cases such as providing connectivity during crowded events,human-instigated disasters,unmanned aerial vehicle traffic management,internet of things in the sky,and situation awareness.4G and 5G cellular networks face various challenges to ensure dynamic control and safe mobility of the drone when it is tasked with delivering these services.The drone can fly in three-dimensional space.The drone connectivity can suffer from increased handover cost due to several reasons,including variations in the received signal strength indicator,co-channel interference offered to the drone by neighboring cells,and abrupt drop in lobe edge signals due to antenna nulls.The baseline greedy handover algorithm only ensures the strongest connection between the drone and small cells so that the drone may experience several handovers.Intended for fast environment learning,machine learning techniques such as Q-learning help the drone fly with minimum handover cost along with robust connectivity.In this study,we propose a Q-learning-based approach evaluated in three different scenarios.The handover decision is optimized gradually using Q-learning to provide efficient mobility support with high data rate in time-sensitive applications,tactile internet,and haptics communication.Simulation results demonstrate that the proposed algorithm can effectively minimize the handover cost in a learning environment.This work presents a notable contribution to determine the optimal route of drones for researchers who are exploring UAV use cases in cellular networks where a large testing site comprised of several cells with multiple UAVs is under consideration.

Investigation and Technological Comparison of 4G and 5G Networks

Mobile cellular data networks have allowed users to access the Internet whilst on the move. Many companies use this technology in their products. Examples of this would be Smart Meters in the home and Tesla cars having their “over the air updates”. Both of these two companies use the 4G and 5G technology. So this report will include a technical overview of the technology and protocols (LTE Advanced) used in 4G and 5G networks and how they provide services to the user and how data is transferred within the networks. And there are lots of different parts about the network architecture between the 4G and 5G systems. This report will talk about some different parts between these two systems and some challenges in them.

A Model Training Method for DDoS Detection Using CTGAN under 5GC Traffic

With the commercialization of 5th-generation mobile communications(5G)networks,a large-scale internet of things(IoT)environment is being built.Security is becoming increasingly crucial in 5G network environments due to the growing risk of various distributed denial of service(DDoS)attacks across vast IoT devices.Recently,research on automated intrusion detection using machine learning(ML)for 5G environments has been actively conducted.However,5G traffic has insufficient data due to privacy protection problems and imbalance problems with significantly fewer attack data.If this data is used to train an ML model,it will likely suffer from generalization errors due to not training enough different features on the attack data.Therefore,this paper aims to study a training method to mitigate the generalization error problem of the ML model that classifies IoT DDoS attacks even under conditions of insufficient and imbalanced 5G traffic.We built a 5G testbed to construct a 5G dataset for training to solve the problem of insufficient data.To solve the imbalance problem,synthetic minority oversampling technique(SMOTE)and generative adversarial network(GAN)-based conditional tabular GAN(CTGAN)of data augmentation were used.The performance of the trained ML models was compared and meaningfully analyzed regarding the generalization error problem.The experimental results showed that CTGAN decreased the accuracy and f1-score compared to the Baseline.Still,regarding the generalization error,the difference between the validation and test results was reduced by at least 1.7 and up to 22.88 times,indicating an improvement in the problem.This result suggests that the ML model training method that utilizes CTGANs to augment attack data for training data in the 5G environment mitigates the generalization error problem.

Compact 5G Vivaldi Tapered Slot Filtering Antenna with Enhanced Bandwidth

Compact fifth-generation(5G)low-frequency band filtering antennas(filtennas)with stable directive radiation patterns,improved bandwidth(BW),and gain are designed,fabricated,and tested in this research.The proposed filtennas are achieved by combining the predesigned compact 5G(5.975–7.125 GHz)third-order uniform and non-uniform transmission line hairpin bandpass filters(UTL and NTL HPBFs)with the compact ultrawide band Vivaldi tapered slot antenna(UWB VTSA)in one module.The objective of this integration is to enhance the performance of 5.975–7.125GHz filtennas which will be suitable for modern mobile communication applications by exploiting the benefits of UWB VTSA.Based on NTL HPBF,more space is provided to add the direct current(DC)biassing circuits in cognitive radio networks(CRNs)for frequency reconfigurable applications.To overcome the mismatch between HPBFs and VTSA,detailed parametric studies are presented.Computer simulation technology(CST)software is used for the simulation in this study.Good measured S11 appeared to be<−13 and<−10.54 dB at 5.48–7.73 and 5.9–7.98GHz with peak realized gains of 6.37 and 6.27 dBi,for VTSA with UTL and NTL HPBFs,respectively which outperforms the predesigned filters.Validation is carried out by comparing the measured and simulated results.

Tackling Key Technological Problems and Advancing 5G Technology Application in Railway

The paper summarizes the development of mobile communication of domestic and foreign railways,and proposes the priorities for tackling key technological problems of railway 5G private network according to the technical routes of railway next-generation mobile communication determined by China State Railway Group Co.,Ltd.From the aspects of work objectives,principles,technical routes and innovative working methods,the paper elaborates the ideas of railway 5G scientific and technological research,puts forward the contents and plans of scientific and technological research on railway 5G private network,systematically organizes the achievements in the scientific and technological research stage of railway 5G private network,and sets forth the key contents of next-step scientific and technological research.

医院5G网络建设标准《基于5G技术的医院网络建设标准》专家解读

2019年在国家卫生健康委指导下,由中日友好医院、国家远程医疗与互联网医学中心、国家基层远程医疗发展指导中心牵头,召集全国30余家省部级医院、中国医学装备协会、中国电信、中国移动、中国联通、华为,联合在中日友好医院联合启动《基于5G技术的医院网络建设标准》。作者就《基于5G技术的医院网络建设标准》制定的背景、核心价值和关键内容进行解读,为本标准的尽快推广及应用提供支持。

5G移动与广播电视融合网络

移动通信技术和智能终端的发展带来了移动互联网时代。第五代移动通信技术(5G)要支持增强移动宽带应用场景,网络流量的绝大部分来自视频类应用,需要以优化的方式传输。广播方式可以用来汇聚视频流量,提高5G网络传输效率。对于广电网络,用户获得信息的行为习惯已经发生改变,广电网络需要开展个性化、交互业务以丰富用户体验。因此,移动和广播电视网络融合逐渐成为信息领域的研究热点。本文从提供视频点播和广播电视业务的角度,通过分析应用场景、业务需求和5G新技术带来的可能性,提出一种5G移动与广播电视融合网络架构。

5G High Mobility Wireless Communications: Challenges and Solutions

The fifth generation(5G) network is expected to support significantly large amount of mobile data traffic and huge number of wireless connections,to achieve better spectrum- and energy-efficiency,as well as quality of service(QoS) in terms of delay,reliability and security.Furthermore,the 5G network shall also incorporate high mobility requirements as an integral part,providing satisfactory service to users travelling at a speed up to 500 km/h.This paper provides a survey of potential high mobility wireless communication(HMWC) techniques for 5G network.After discussing the typical requirements and challenges of HMWC,key techniques to cope with the challenges are reviewed,including transmission techniques under the fast timevarying channels,network architecture with mobility support,and mobility management.Finally,future research directions on 5G high mobility communications are given.

基于5G的天空地一体化战术通信研究

现有战术通信主要依靠窄带通信技术实现,难以满足战场大量信息的分发需求。利用民用技术加速战术通信的发展已经取得业界的广泛认同,但是移动通信固有的特点使得这一进程非常缓慢。5G移动通信的提出为此提供了一次新的契机。初步探讨5G军用化的可行性,发现利用5G的关键技术并经过特殊设计可以消除/缓解传统移动通信军用化存在的一些障碍;并基于5G提出了一种天空地一体化战术通信网络,为战术通信的未来发展提供了一种新思路。