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 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.

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.

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.

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.

Native intelligence for 6G mobile network: technical challenges,architecture and key features

The application of the artificial intelligence(AI) technology in the 5 th generation mobile communication system(5 G) networks promotes the development of the mobile communication network and its application in vertical industries, however, the application models of "patching" and "plug-in" have hindered the effect of AI applications. Meanwhile, the application of AI in all walks of life puts forward requirements for new capabilities of the future network, such as distributed training, real-time collaborative inference, local data processing, etc., which require "native intelligence design" in future networks. This paper discusses the requirements of native intelligence in the 6 th generation mobile communication system(6 G) networks from the perspectives of 5 G intelligent network challenges and the "ubiquitous intelligence" vision of 6 G, and analyzes the technical challenges of the AI workflows in its lifecycle and the AI as a service(AIaaS) in cloud network. The progress and deficiencies of the current research on AI functional architecture in various industry organizations are summarized. The end-to-end functional architecture for native AI for 6 G network and its three key technical characteristics are proposed: quality of AI services(QoAIS) based AI service orchestration for its full lifecycle, deep integration of native AI computing and communication, and integration of native AI and digital twin network. The directions of future research are also prospected.

Survey on Reinforcement Learning Applications in Communication Networks

In recent years,intelligent communication has drawn huge research efforts in both academia and industry.With the advent of 5G technology,intelligent wireless terminals and intelligent communication networks are increasingly under intensive study.Artificial intelligence enhances the network capability with automatic and adaptive adjustment.Reinforcement learning(RL)and deep reinforcement learning(DRL)are two powerful techniques in artificial intelligence which can learn the optimal decision according to the environment feedback.In this paper,we focus on the latest research progress on RL and DRL applied in three emerging technologies including mobile edge computing(MEC),software defined network(SDN)and network virtualization in 5G.The prospect of further research and development in the future is preliminarily forecasted.

Next Decade of Telecommunications Artificial Intelligence

It has been an exciting journey since the mobile communications and artificial intelligence(AI)were conceived in 1983 and 1956.While both fields evolved independently and profoundly changed communications and computing industries,the rapid convergence of 5th generation mobile communication technology(5G)and AI is beginning to significantly transform the core communication infrastructure,network management,and vertical applications.The paper first outlined the individual roadmaps of mobile communications and AI in the early stage,with a concentration to review the era from 3rd generation mobile communication technology(3G)to 5G when AI and mobile communications started to converge.With regard to telecommunications AI,the progress of AI in the ecosystem of mobile communications was further introduced in detail,including network infrastructure,network operation and management,business operation and management,intelligent applications towards business supporting system(BSS)&operation supporting system(OSS)convergence,verticals and private networks,etc.Then the classifications of AI in telecommunication ecosystems were summarized along with its evolution paths specified by various international telecommunications standardization organizations.Towards the next decade,the prospective roadmap of telecommunications AI was forecasted.In line with 3rd generation partnership project(3GPP)and International Telecommunication Union Radiocommunication Sector(ITU-R)timeline of 5G&6th generation mobile communication technology(6G),the network intelligence following 3GPP and open radio access network(O-RAN)routes,experience and intent-based network management and operation,network AI signaling system,intelligent middle-office based BSS,intelligent customer experience management and policy control driven by BSS&OSS convergence,evolution from service level agreement(SLA)to experience level agreement(ELA),and intelligent private network for verticals were further explored.The paper is concluded with the vision that AI will reshape the future beyond 5G(B5G)/6G landscape,and we need pivot our research and development(R&D),standardizations,and ecosystem to fully take the unprecedented opportunities.