Wideband Reconfigurable Millimeter-Wave Linear Array Antenna Using Liquid Crystal for 5G Networks

The advanced design of a 10 × 1 linear antenna array system with the capa-bility of frequency tunability using GT3-23001 liquid crystal (LC) is pro-posed. The design for this reconfigurable wideband antenna array for 5G ap-plications at Ka-band millimeter-wave (mmw) consists of a double layer of stacked patch antenna with aperture coupled feeding. The bias voltage over LC varies from 0 V to 10.6 V to achieve a frequency tunability of 1.18 GHz. The array operates from 25.3 GHz to 33.8 GHz with a peak gain of 19.2 dB and a beamwidth of 5.2° at 30 GHz. The proposed reconfigurable antenna ar-ray represents a real and efficient solution for the recent and future mmw 5G networks. The proposed antenna is suitable for 5G base stations in stadiums, malls and convention centers. It is proper for satellite communications and radars at mmw.

Potential friendship discovery in social networks based on hybrid ensemble multiple collaborative filtering models in a 5G network environment

At present, 5G network technology is being applied to various social network modes, and it can provide technical and traffic support for social networks. Potential friendship discovery technology in 5G-enabled social networks is beneficial for users to make potential friends and expand their range of activities and social hierarchy, which is highly sought after in today's social networks and has great economic and application value. However, the sparsity of the dominant user association dataset in 5G-enabled social networks and the limitations of traditional collaborative filtering algorithms are two major challenges for the friend recommendation problem. Therefore, in order to overcome these problems regarding previous models, we propose a Hybrid Ensemble Multiple Collaborative Filtering Model (HEMCF) for discovering potential buddy relationships. The HEMCF model draws on a special autoencoder method that can effectively exploit the association matrix between friends and additional information to extract a hidden representation of users containing global structural information. Then, it uses the random walk-based graph embedding algorithm DeepWalk to extract another hidden representation of users in the buddy network containing local structural information. Finally, in the output module, the HEMCF model stacks and multiplies the two types of hidden representations of users to ensure that the information mentioned above is concentrated in the final output to generate the final prediction value. The magnitude of the prediction value represents the probability of the users being friends, with larger values representing a high probability of the two users being friends, and vice versa. Experimental results show that the proposed method boosts the accuracy of the relationship prediction over baselines on 3 real-world public datasets dramatically.

Fault Diagnosis of 5G Networks Based on Digital Twin Model

Fault diagnosis of 5G networks faces the challenges of heavy reliance on human experience and insufficient fault samples and relevant monitoring data.The digital twin technology can realize the interaction between virtual space and physical space through the fusion of model and data,providing a new paradigm for fault diagnosis.In this paper,we first propose a network digital twin model and apply it to 5G network diagnosis.We then use an improved Average Wasserstein GAN with Gradient Penalty(AWGAN-GP)method to discover and predict failures in the twin network.Finally,we use XGBoost algorithm to locate the faults in physical network in real time.Extensive simulation results show that the proposed approach can significantly increase fault prediction and diagnosis accuracy in the case of a small number of labeled failure samples in 5G networks.

Resource Allocation and Optimization in Device-to-Device Communication 5G Networks

The next-generation wireless networks are expected to provide higher capacity,system throughput with improved energy efficiency.One of the key technologies,to meet the demand for high-rate transmission,is deviceto-device(D2D)communication which allows users who are close to communicating directly instead of transiting through base stations,and D2D communication users to share the cellular user chain under the control of the cellular network.As a new generation of cellular network technology,D2D communication technology has the advantages of improving spectrum resource utilization and improving system throughput and has become one of the key technologies that have been widely concerned in the industry.However,due to the sharing of cellular network resources,D2D communication causes severe interference to existing cellular systems.One of the most important factors in D2D communication is the spectrum resources utilization and energy consumption which needs considerable attention from research scholars.To address these issues,this paper proposes an efficient algorithm based on the idea of particle swarm optimization.The main idea is to maximize the energy efficiency based on the overall link optimization of D2D user pairs by generating an allocation matrix of spectrum and power.The D2D users are enabled to reuse multiple cellular user’s resources by enhancing their total energy efficiency based on the quality of service constraints and the modification of location and speed in particle swarm.Such constraint also provides feasibility to solve the original fractional programming problem.Simulation results indicate that the proposed scheme effectively improved the energy efficiency and spectrum utilization as compared with other competing alternatives.

Feasibility and Challenges of 5G Network Deployment in Least Developed Countries (LDC)

Growing client population, ever-increasing service demand, and complexity of services are the driving factors for the mobile operators for a paradigm shift in their core technology and radio access networks. 5G mobile network is the result of this paradigm shift and currently under deployment in many developed countries such as United States, United Kingdom, South Korea, Japan, and China—to name a few. However, most of the Least Developed Countries (LDCs) have very recently been implemented 4G mobile networks for which the overall role out phase is still not complete. In this paper, we investigate how feasible it is for LDCs to emphasize on a possible deployment of 5G networks at the moment. At first, we take a holistic approach to show the major technical challenges LDCs are likely to face while deploying the 5G mobile networks. Then we argue that various security aspects of 5G networks are an ongoing issue and LDCs are not technologically competent to handle many security glitches of 5G networks. At the same time, we show that most of the use cases of 5G networks are not applicable in the context of many LDCs (at least at the present time). Finally, this paper concludes that the start of the 5G network deployment in LDCs would take much longer time than expected.

A Game Theoretic Approach for Hierarchical Caching Resource Sharing in 5G Networks with Virtualization

Caching and virtualization have been considered as the promising techniques in 5G Networks. In 5G networks with virtualization, the caching resources deployed by infrastructure providers (InPs) can be abstracted into isolated slices and transparently shared by mobile virtual network operators (MVNOs). In this case, one of the most important issues is how the MVNOs to share the caching resource. To solve this issue, different from previous works, a hierarchical caching architecture that core network and radio access network (RAN) have the caching capability in 5G networks with virtualization is first considered in this paper. Then, we study the problem of hierarchical caching resource sharing for MVNOs, and a competitive game to maximize their expectation revenue based on the oligopoly market model is formulated. As it is a hard problem to find the optimal solution in the hierarchical caching resource sharing problem, we decompose the optimization problem into two independent caching resource sharing problems in RAN and core network, respectively. Then the local optimal solutions are solved and the global Nash equilibrium solution is achieved. Finally, simulation results are illustrated to demonstrate the performance of the proposed scheme.

Virtual 5G Network Embedding in a Heterogeneous and Multi-Domain Network Infrastructure

The pursuit of the higher performance mobile communications forces the emergence of the fifth generation mobile communication(5G). 5G network, integrating wireless and wired domain, can be qualified for the complex virtual network work oriented to the cross-domain requirement. In this paper, we focus on the multi-domain virtual network embedding in a heterogeneous 5G network infrastructure, which facilitates the resource sharing for diverse-function demands from fixed/mobile end users. We proposed the mathematical ILP model for this problem.And based on the layered-substrate-resource auxiliary graph and an effective six-quadrant service-type-judgment method, 5G embedding demands can be classified accurately to match different user access densities. A collection of novel heuristic algorithms of virtual 5G network embedding are proposed. A great deal of numerical simulation results testified that our algorithm performed better in terms of average blocking rate, routing latency and wireless/wired resource utilization, compared with the benchmark.

Book Review-5G Network Architecture

5G is the hottest topic in telecommunication area in recent years.ITU has defined 5G as IMT-2020,and presented the scenarios of IMT-2020.These scenarios for IMT-2020 can be concluded as follows：-Enhanced Mobile Broadband：Mobile Broadband addresses the human-centric use cases for access to multi-media content,services and data.The demand for mobile

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.

Planning and Profit Sharing in Overlay WiFi and LTE Systems toward 5G Networks

With the increasing demand for data traffic and with the massive foreseen deployment of the Internet of Things (IoT), higher data rates and capacity are required in mobile networks. While Heterogeneous Networks (HetNets) are under study toward 5G technology, Wireless Fidelity (WiFi) Access Points (APs) are considered a potential layer within those multiple Radio Access Technologies (RATs). For this purpose, we have proposed in this paper a novel WiFi dimensioning method, to offload data traffic from Long Term Evolution (LTE) to WiFi, by transferring the LTE energy consuming heavy users, to the WiFi network. First, we have calculated the remaining available capacity of the WiFi network based on the estimated load of each WiFi physical channel using the overlapping characteristic of the channels. Then, we were able through this dimensioning method, to calculate the minimum needed number of WiFi APs that ensure the same or better throughput for the LTE transferred users. By this method, we have ensured additional capacity in the LTE network with minimum investment cost in the WiFi network. Finally, we have estimated the profit sharing between LTE and WiFi by considering data bundles subscription revenues and the infrastructure capital and operational costs. We have calculated for each network the profit share using a coalition game theory Shapley value that pinpoints the benefit of the cooperation using the proposed dimensioning method.

Machine Learning Based Classifiers for QoE Prediction Framework in Video Streaming over 5G Wireless Networks

Recently,the combination of video services and 5G networks have been gaining attention in the wireless communication realm.With the brisk advancement in 5G network usage and the massive popularity of threedimensional video streaming,the quality of experience(QoE)of video in 5G systems has been receiving overwhelming significance from both customers and service provider ends.Therefore,effectively categorizing QoE-aware video streaming is imperative for achieving greater client satisfaction.This work makes the following contribution:First,a simulation platform based on NS-3 is introduced to analyze and improve the performance of video services.The simulation is formulated to offer real-time measurements,saving the expensive expenses associated with real-world equipment.Second,A valuable framework for QoE-aware video streaming categorization is introduced in 5G networks based on machine learning(ML)by incorporating the hyperparameter tuning(HPT)principle.It implements an enhanced hyperparameter tuning(EHPT)ensemble and decision tree(DT)classifier for video streaming categorization.The performance of the ML approach is assessed by considering precision,accuracy,recall,and computation time metrics for manifesting the superiority of these classifiers regarding video streaming categorization.This paper demonstrates that our ML classifiers achieve QoE prediction accuracy of 92.59%for(EHPT)ensemble and 87.037%for decision tree(DT)classifiers.

配电网5G通信架构及其时延可靠性研究

5G在数字配电网领域的核心价值在于发挥5G的超高可靠、低时延技术优势,为配电网涉控业务提供高可靠、低时延的通信。为了系统地提供配电网5G通信时延与可靠性理论分析方案,结合数字配电网业务给出了配电网5G通信典型架构,深入分析了针对配电网5G通信的时延模型,针对国内四大运营商5G帧结构逐一进行了端到端时延分析,并通过5G链路级仿真了3GPP Rel-15和Rel-16的5G可靠性数值,提出了配电网5G通信的时延与可靠性联合分析方法。

Optical Neural Networks:Analysis and Prospects for 5G Applications

With the capacities of self-learning,acquainted capacities,high-speed looking for ideal arrangements,solid nonlin-ear fitting,and mapping self-assertively complex nonlinear relations,neural systems have made incredible advances and accomplished broad application over the final half-century.As one of the foremost conspicuous methods for fake insights,neural systems are growing toward high computational speed and moo control utilization.Due to the inborn impediments of electronic gadgets,it may be troublesome for electronic-implemented neural systems to make the strides these two exhibitions encourage.Optical neural systems can combine optoelectronic procedures and neural organization models to provide ways to break the bottleneck.This paper outlines optical neural networks of feedforward repetitive and spiking models to give a clearer picture of history,wildernesses,and future optical neural systems.The framework demonstrates neural systems in optic communication with the serial and parallel setup.The graphene-based laser structure for fiber optic communication is discussed.The comparison of different balance plans for photonic neural systems is made within the setting of hereditary calculation and molecule swarm optimization.In expansion,the execution comparison of routine photonic neural,time-domain with and without extending commotion is additionally expounded.The challenges and future patterns of optical neural systems on the growing scale and applications of in situ preparing nonlinear computing will hence be uncovered.

Multi-Hop Transmission Method of 5G Millimeter Wave Relay Based on Network Coding

With the rapid development of the Internet technology,millimeter wave(mmWave)will be used as a supplement to 5G low frequency bands to meet the extremely high system capacity requirements of 5G in hot spots.Although 5G mmWave communication can adapt to the needs of 5G network and carry a large amount of transmitted data,transmission stability has become one of the key technical issues of 5G network mmWave communication due to problems such as strong attenuation and poor penetration of mmWave.In order to improve the efficiency of the mmWave multi-hop transmission,we propose a 5G mmWave multi-hop transmission method based on network coding,which can adapt to the current wireless network environment,improve spectrum efficiency and increase network throughput.Based on MATLAB simulation experiments,it is verified that the proposed method can greatly improve the transmission efficiency and reduce the signal loss under the premise of ensuring the accurate signal transmission.

Power Allocation in NOMA-CR for 5G Enabled IoT Networks

In the power domain,non-orthogonal multiple access(NOMA)supports multiple users on the same time-frequency resources,assigns different transmission powers to different users,and differentiates users by user channel gains.Multi-user signals are superimposed and transmitted in the power domain at the transmitting end by actively implementing controllable interference information,and multi-user detection algorithms,such as successive interference cancellation(SIC)is performed at the receiving end to demodulate the necessary user signals.In contrast to the orthogonal transmission method,the non-orthogonal method can achieve higher spectrum utilization.However,it will increase the receiver complexity.With the development of microelectronics technology,chip processing capabilities continue to increase,laying the foundation for the practical application of non-orthogonal transmission technology.In NOMA,different users are differentiated by different power levels.Therefore,the power allocation has a considerable impact on the NOMA system performance.To address this issue,the idea of splitting power into two portions,intra-subbands and intersubbands,is proposed in this study as a useful algorithm.Then,such optimization problems are solved using proportional fair scheduling and water-filling algorithms.Finally,the error propagation was modeled and analyzed for the residual interference.The proposed technique effectively increased the system throughput and performance under various operating settings according to simulation findings.A comparison is performed with existing algorithms for performance evaluation.

An Optimized Approach for Spectrum Utilization in mmWave Massive MIMO 5G Wireless Networks

Massive multiple-input multiple-output(MIMO)systems that use the millimeter-wave(mm-wave)band have a higher frequency and more antennas,which leads to significant path loss,high power consumption,and server interference.Due to these issues,the spectrum efficiency is significantly reduced,making spectral efficiency improvement an important research topic for 5G communication.Together with communication in the terahertz(THz)bands,mmWave communication is currently a component of the 5G standards and is seen as a solution to the commercial bandwidth shortage.The quantity of continuous,mostly untapped bandwidth in the 30–300 GHz band has presented a rare opportunity to boost the capacity of wireless networks.The wireless communications and consumer electronics industries have recently paid a lot of attention to wireless data transfer and media streaming in the mmWave frequency range.Simple massive MIMO beamforming technology cannot successfully prevent interference between multiple networks in the current spectrum-sharing schemes,particularly the complex interference dispersed in indoor communication systems such as homes,workplaces,and stadiums.To effectively improve spectrum utilization and reduce co-channel interference,this paper proposes a novel algorithm.The main idea is to utilize the spectrum in software-defined mmWave massive MIMO networks through coordinated and unified management.Then,the optimal interference threshold is determined through the beam alignment method.Finally,a greedy optimization algorithm is used to allocate optimal spectral resources to the users.Simulation results show that the proposed algorithm improved spectral efficiency and reduced interference.

5G高铁专网覆盖综合解决方案研究和应用

5G高铁覆盖面临着资源占时短、瞬时容量高、车体损耗大、移动速度快、基站交替快和远近兼顾难等多重挑战。本文针对5G高铁专网的覆盖方案、容量方案、公专网频率协同方案、主设备与天线选型方案、优化创新方案五大关键点开展了对比论证和深入研究,并应用于某高铁规划建设优化实践中,提升了高铁客户的感知,满足了“5G高铁上车”过渡期的高铁场景5G覆盖需求,为后续高铁覆盖项目的应用推广提供了重要的参考。

基于5G网络的RedCap部署方案研究

RedCap作为轻量化的5G技术,是5G Rel-17版本定义的新终端类型,可有效兼顾行业对于技术性能和部署成本的并存需求。一般认为,这种轻量级5G技术的核心价值在于与5G NR网络优异特性的融合,即如何基于运营商已部署的5G无线网引入RedCap是其中的关键问题。结合运营商无线网现状,通过分析RedCap与无线网络侧相关的功能特性,提出引入RedCap后的无线网组网部署方案,包括无线网升级方案、参数配置方案以及信令开销策略等,可为国内各运营商在方案制定及工程实施上提供参考。

Artificial Intelligence Self-Organising (AI-SON) Frameworks for 5G-Enabled Networks: A Review

The fifth generation (5G) networks will support the rapid emergence of Internet of Things (IoT) devices operating in a heterogeneous network (HetNet) system. These 5G-enabled IoT devices will result in a surge in data traffic for Mobile Network Operators (MNOs) to handle. At the same time, MNOs are preparing for a paradigm shift to decouple the control and forwarding plane in a Software-Defined Networking (SDN) architecture. Artificial Intelligence powered Self-Organising Networks (AI-SON) can fit into the SDN architecture by providing prediction and recommender systems to minimise costs in supporting the MNO’s infrastructure. This paper presents a review report on AI-SON frameworks in 5G and SDN. The review considers the dynamic deployment and functions of the AI-SON frameworks, especially for SDN support and applications. Each module in the frameworks was discussed to ascertain its relevance based on the context of AI-SON and SDN integration. After examining each framework, the identified gaps are summarised as open issues for future works.

5G/B5G异构网络切换过程分析和移动性管理解决方案

有效的移动性管理对于确保5G异构网络预期的QoS和QoE至关重要。切换过程在移动性管理中起着至关重要的作用。在此过程中的故障可能会对5G通信网络的可靠性、稳定性和连接性产生不利影响。对5G HetNet的切换过程进行了分析,包括5G切换过程步骤、5G HetNet的三层切换、5G HetNet的关键切换参数。此外,针对具体问题,如超高速、负载均衡和小区间干扰,归纳总结了5G HetNet的移动性管理主要解决方案,并提出了5G/B5G HetNet的移动性管理新方法。