Addressing the Issues and Developments Correlated with Envisaged 5G Mobile Technologies: Comprehensive Solutions

Fifth Generation(5G)communications are regarded as the cornerstone to household consumer experience improvements and smart manufacturing revolution from the standpoint of industries’objectives.It is anticipated that Envisaged 5G(E5G)mobile technology would be operational in certain developed countries by 2023.The Internet of Things(IoTs)will transform how humans live when combined with smart and integrated sensing devices,such as in-home sensing devices.Recent research is being carried out all over the world to produce a new technique that can be crucial in the success of the anticipated 5G mobile technology.High output,reduced latency,highly reliable,greater scalability,high performance,capacity,bandwidth efficiency,virtual open-air transmission,and efficient energy mobile wireless communications are all being investigated currently.In this work,a comprehensive path for addressing the difficulties and developments associated with 5G mobile technology is provided.The debate and description of a complete analysis of current situations,certain characteristics and prospective scenarios,important technologies,problems and advances,and spectrum allocation of envisioned 5G mobile technologies are provided.Furthermore,this paper analyzes the most notable elements of 5G mobile technology,such as Cognitive Radio(CR),flexibility,accessibility,and cloud-based service offers,which will assure 5G mobile technology’s dominance as the main protocol for international communication.Eventually,this paper provides a method for integrating CR with current wireless communication systems,the necessity for further evolution of the E5G network,and the need for comprehensive consideration of architecture evolution and function enhancement to enhance the E5G mobile technologies.

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.

5G技术对车联网路径规划的影响

随着5G通信技术与车联网技术的日趋成熟,车联网路径规划从二维路径规划向智能多元立体路径规划发展,车路协同环境的资源利用需求渐增。因此,将通信技术与车联网融合的实时高速率信息交互作为车联网路径规划的技术支撑具有十分重要的意义。在此背景下,分析了5G技术对车联网路径规划的影响,探究其高速数据传输和低时延等一系列技术对于车联网立体路径规划发展的推动,为路径规划提供更加准确和个性化的导航建议和路径选择奠定基础。

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.

System Integration of Terrestrial Mobile Communication and Satellite Communication——The Trends, Challenges and Key Technologies in B5G and 6G

Mobile communication standards have been developed into a new era of B5G and 6G.In recent years,low earth orbit(LEO)satellites and space Internet have become hot topics.The integrated satellite and terrestrial systems have been widely discussed by industries and academics,and even are expected to be applied in those huge constellations in construction.This paper points out the trends of two stages towards system integration of the terrestrial mobile communication and the satellite communications:to be compatible with 5G,and to be integrated within 6G.Based on analysis of the challenges of both stages,key technologies are thereafter analyzed in detail,covering both air interface currently discussed in 3GPP for B5G and also novel network architecture and related transmission technologies toward future 6G.

Mobile Web Augmented Reality in 5G and Beyond:Challenges, Opportunities, and Future Directions

The popularity of wearable devices and smartphones has fueled the development of Mobile Augmented Reality(MAR),which provides immersive experiences over the real world using techniques,such as computer vision and deep learning.However,the hardware-specific MAR is costly and heavy,and the App-based MAR requires an additional download and installation and it also lacks cross-platform ability.These limitations hamper the pervasive promotion of MAR.This paper argues that mobile Web AR(MWAR)holds the potential to become a practical and pervasive solution that can effectively scale to millions of end-users because MWAR can be developed as a lightweight,cross-platform,and low-cost solution for end-to-end delivery of MAR.The main challenges for making MWAR a reality lie in the low efficiency for dense computing in Web browsers,a large delay for real-time interactions over mobile networks,and the lack of standardization.The good news is that the newly emerging 5G and Beyond 5G(B5G)cellular networks can mitigate these issues to some extent via techniques such as network slicing,device-to-device communication,and mobile edge computing.In this paper,we first give an overview of the challenges and opportunities of MWAR in the 5G era.Then we describe our design and development of a generic service-oriented framework(called MWAR5)to provide a scalable,flexible,and easy to deploy MWAR solution.We evaluate the performance of our MWAR5 system in an actually deployed 5G trial network under the collaborative configurations,which shows encouraging results.Moreover,we also share the experiences and insights from our development and deployment,including some exciting future directions of MWAR over 5G and B5G networks.

Radio Propagation and Wireless Coverage of LSAA-Based 5G Millimeter-Wave Mobile Communication Systems

Millimeter-wave(mm Wave) communications will be used in fifth-generation(5G) mobile communication systems, but they experience severe path loss and have high sensitivity to physical objects, leading to smaller cell radii and complicated network architectures. A coverage extension scheme using large-scale antenna arrays(LSAAs) has been suggested and theoretically proven to be cost-efficient in combination with ultradense small cell networks. To analyze and optimize the LSAA-based network deployments, a comprehensive survey of recent advances in statistical mmWave channel modeling is first presented in terms of channel parameter estimation, large-scale path loss models, and small-scale cluster models. Next, the measurement and modeling results at two 5G candidate mmWave bands(e.g., 28 GHz and 39 GHz) are reviewed and compared in several outdoor scenarios of interest, where the propagation characteristics make crucial contributions to wireless network designs. Finally, the coverage behaviors of systems employing a large number of antenna arrays are discussed, as well as some implications on future mmWave cellular network designs.

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.

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.

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.

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.

A Novel 28 GHz Phased Array Antenna for 5G Mobile Communications

A novel phased array antenna consisting of 256 elements is presented and experimentally verified for 5G millimeter-wave wireless communications.The antenna integrated with a wave control circuit can perform real-time beam scanning by reconfiguring the phase of an antenna unit.The unit,designed at 28 GHz using a simple patch structure with one PIN diode,can be electronically controlled to generate 1 bit phase quantization.A prototype of the antenna is fabricated and measured to demonstrate the feasibility of this approach.The measurement results indicate that the antenna achieves high gain and fast beam-steering,with the scan beams within±60°range and the maximum gain up to 21.7 dBi.Furthermore,it is also tested for wireless video transmission.In ZTE Shanghai,the antenna was used for the 5G New Radio(NR)test.The error vector magnitude(EVM)is less than 3%and the adjacent channel leakage ratio(ACLR)less than−35 dBc,which can meet 5G system requirements.Compared with the conventional phased array antenna,the proposed phased array has the advantages of low power consumption,low cost and conformal geometry.Due to these characteristics,the antenna is promising for wide applications in 5G millimeter-wave communication systems.

Demand-aware mobile bike-sharing service using collaborative computing and information fusion in 5G IoT environment

Mobile bike-sharing services have been prevalently used in many cities as an important urban commuting service and a promising way to build smart cities,especially in the new era of 5G and Internet-of-Things(IoT)environments.A mobile bike-sharing service makes commuting convenient for people and imparts new vitality to urban transportation systems.In the real world,the problems of no docks or no bikes at bike-sharing stations often arise because of several inevitable reasons such as the uncertainty of bike usage.In addition to pure manual rebalancing,in several works,attempts were made to predict the demand for bikes.In this paper,we devised a bike-sharing service with highly accurate demand prediction using collaborative computing and information fusion.We combined the information of bike demands at different time periods and the locations between stations and proposed a dynamical clustering algorithm for station clustering.We carefully analyzed and discovered the group of features that impact the demand of bikes,from historical bike-sharing records and 5G IoT environment data.We combined the discovered information and proposed an XGBoost-based regression model to predict the rental and return demand.We performed sufficient experiments on two real-world datasets.The results confirm that compared to some existing methods,our method produces superior prediction results and performance and improves the availability of bike-sharing service in 5G IoT environments.

A Compact Self-Isolated MIMO Antenna System for 5G Mobile Terminals

A compact self-isolated Multi Input Multi Output (MIMO) antennaarray is presented for 5G mobile phone devices. The proposed antenna systemis operating at the 3.5 GHz band (3400–3600 MHz) and consists of eight antennaelements placed along two side edges of a mobile device, which meets the currenttrend requirements of full-screen smartphone devices. Each antenna element isdivided into two parts, a front part and back part. The front part consists of anI-shaped feeding line and a modified Hilbert fractal monopole antenna, whereasthe back part is an L-shaped element shorted to the system ground by a0.5 mm short stub. A desirable compactness can be obtained by utilizing the Hilbert space-filling property where the antenna element’s overall planar size printedon the side-edge frame is just (9.57 mm × 5.99 mm). The proposed MIMO antenna system has been simulated, analyzed, fabricated and tested. Based on the selfisolated property, good isolation (better than 15 dB) is attained without employingadditional decoupling elements and/or isolation techniques, which increases system complexity and reduces the antenna efficiency. The scattering parameters,antenna efficiencies, antenna gains, and antenna radiation characteristics areinvestigated to assess the proposed antenna performance. For evaluating the proposed antenna array system performance, the Envelope Correlation Coefficients(ECCs), Mean Effective Gains (MEGs) and channel capacity are calculated.Desirable antenna and MIMO performances are evaluated to confirm the suitability of the proposed MIMO antenna system for 5G mobile terminals.

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.

Edge Computing Platform with Efficient Migration Scheme for 5G/6G Networks

Next-generation cellular networks are expected to provide users with innovative gigabits and terabits per second speeds and achieve ultra-high reliability,availability,and ultra-low latency.The requirements of such networks are the main challenges that can be handled using a range of recent technologies,including multi-access edge computing(MEC),artificial intelligence(AI),millimeterwave communications(mmWave),and software-defined networking.Many aspects and design challenges associated with the MEC-based 5G/6G networks should be solved to ensure the required quality of service(QoS).This article considers developing a complex MEC structure for fifth and sixth-generation(5G/6G)cellular networks.Furthermore,we propose a seamless migration technique for complex edge computing structures.The developed migration scheme enables services to adapt to the required load on the radio channels.The proposed algorithm is analyzed for various use cases,and a test bench has been developed to emulate the operator’s infrastructure.The obtained results are introduced and discussed.

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.

Fuzzy Logic Based Handover Authentication in 5g Telecommunication Heterogeneous Networks

Under various deployment circumstances,fifth-generation(5G)telecommunications delivers improved network compound management with fast communication channels.Due to the introduction of the Internet of Things(IoT)in data management,the majority of the ultra-dense network models in 5G networks frequently have decreased spectral efficiency,weak handover management,and vulnerabilities.The majority of traditional handover authentication models are seriously threatened,making them vulnerable to a variety of security attacks.The authentication of networked devices is the most important issue.Therefore,a model that incorporates the handover mechanism and authentication model must be created.This article uses a fuzzy logic model to create a handover and key management system that focuses on cloud handover management and authentication performance.In order to decrease delays in 5G networks,the fuzzy logic is built with multiple criteria that aim to reduce the number of executed handovers and target cell selection.The simulation is run to evaluate the model’s performance in terms of latency,spatial complexity,and other metrics related to authentication attack validation.

Computer Modelling of Compact 28/38 GHz Dual-Band Antenna for Millimeter-Wave 5G Applications

A four-element compact dual-band patch antenna having a common ground plane operating at 28/38 GHz is proposed formillimeter-wave communication systems in this paper.Themultiple-input-multiple-output(MIMO)antenna geometry consists of a slotted ellipse enclosed within a hollow circle which is orthogonally rotated with a connected partial ground at the back.The overall size of the four elements MIMO antenna is 2.24λ×2.24λ(at 27.12GHz).The prototype of four-element MIMOresonator is designed and printed using Rogers RTDuroid 5880 withε_(r)=2.2 and loss tangent=0.0009 and having a thickness of 0.8 mm.It covers dual-band having a fractional bandwidth of 15.7%(27.12-31.34 GHz)and 4.2%(37.21-38.81 GHz)for millimeter-wave applications with a gain of more than 4 dBi at both bands.The proposed antenna analysis in terms ofMIMOdiversity parameters(Envelope Correlation Coefficient(ECC)and Diversity Gain(DG))is also carried out.The experimental result in terms of reflection coefficient,radiation pattern,gain and MIMOdiversity parameter correlates very well with the simulated ones that show the potential of the proposed design for MIMO applications at millimeter-wave frequencies.

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.