Future Mobile Terminal and Network Access Architecture for China 4G Open Mobile Communications

This paper relates to an advanced open mobile communication system and method of integrating the mobile communications, wireless access systems and wired communications into one common platform architecture for China's 4th generation mobile communications, supporting costeffective broadband voice, data and video services in wireless, mobile and wired environment with one single integrated mobile terminal device. The paper includes new architecture in the integrated mobile device and converged network access, and minimum modifi cation in the existing mobile telecommunication infrastructures. This paper introduces the long-term evolution strategy for China's TDD system platform towards China's future 4G mobile communications.

Business Ecosystem Strategies of Mobile Network Operators in the 3G Era

This paper applies the perspective of business ecosystem to mobile communications industry,trying to help mobile network operators improve their strategies in the era of the third generation mobile communications(3G).According to the definition of the business ecosystem,the ecosystem structure of mobile network operators is analyzed.As an important hub in the ecosystem,mobile network operators are advised to take a keystone strategy.The key points of the strategy are summarized.Finally,suggestions for Chinese mobile network operators are given based on the analysis.

Design Framework of Unsourced Multiple Access for 6G Massive IoT

In this paper,ambient IoT is used as a typical use case of massive connections for the sixth generation(6G)mobile communications where we derive the performance requirements to facilitate the evaluation of technical solutions.A rather complete design of unsourced multiple access is proposed in which two key parts:a compressed sensing module for active user detection,and a sparse interleaver-division multiple access(SIDMA)module are simulated side by side on a same platform at balanced signal to noise ratio(SNR)operating points.With a proper combination of compressed sensing matrix,a convolutional encoder,receiver algorithms,the simulated performance results appear superior to the state-of-the-art benchmark,yet with relatively less complicated processing.

基于4G的机器人与云平台无线数据传输系统设计

将机器人采集到的温度、湿度和位置等数据信息传送至云平台服务器,便于云端数据分析、机器人数据共享以及人机信息交互等。本文应用第4代移动通信技术(the 4th generation mobile communication technology,4G)无线传输技术,设计的机器人与云平台无线数据传输系统主要包括硬件和软件实现2个部分,硬件方面机器人通过32位微控制器(STMicroelectronics32,STM32)嵌入式系统与4G模块组合,将传感器采集到的数据信息,通过Internet网络传输到云平台服务器中,软件部分运用C语言编程通过网络透传模式(transmission control protocol/user datagram protocol, TCP/UDP)实现无线通信过程,最终实验验证了机器人与云平台服务器之间的双向无线数据传输功能。

Performance Evaluation of Scheduling Algorithms for 4G (LTE)

Long Term Evolution (LTE) is designed to revolutionize mobile broadband technology with key considerations of higher data rate, improved power efficiency, low latency and better quality of service. This work analyzes the impact of resource scheduling algorithms on the performance of LTE (4G) and WCDMA (3G) networks. In this paper, a full illustration of LTE system is given together with different scheduling algorithms. Thereafter, 3G WCDMA and 4G LTE networks were simulated using Simulink simulator embedded in MATLAB and performance evaluations were carried out. The performance metrics used for the evaluations are average system throughput, packet delay, latency and allocation of fairness using Round Robin, Best CQI and Proportional fair Packet Scheduling Algorithms. The results of the evaluations on both networks were analysed. The results showed that 4G LTE network performs better than 3G WCDMA network in all the three scheduling algorithms used.

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.

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.

地震台站无线远程监控及3G备用信道方案实现

介绍了一稳定可靠的地震台站无线远程监控及3G备用信道方案的实现,其是基于GSM(全球移动通信系统)网络3G(第三代移动通信技术)和SMS(短信业务)的方案。当有线信道出现故障时,中心人员可通过SMS(短信业务)指令对其控制切换并启动无线备用信道,当有线信道恢复后,通过指令关闭无线信道并切换至有线信道进行地震数据传输。具有通过3G无线传输测震数据的功能。

Spatio-Temporal Cellular Network Traffic Prediction Using Multi-Task Deep Learning for AI-Enabled 6G

Spatio-temporal cellular network traffic prediction at wide-area level plays an important role in resource reconfiguration,traffic scheduling and intrusion detection,thus potentially supporting connected intelligence of the sixth generation of mobile communications technology(6G).However,the existing studies just focus on the spatio-temporal modeling of traffic data of single network service,such as short message,call,or Internet.It is not conducive to accurate prediction of traffic data,characterised by diverse network service,spatio-temporality and supersize volume.To address this issue,a novel multi-task deep learning framework is developed for citywide cellular network traffic prediction.Functionally,this framework mainly consists of a dual modular feature sharing layer and a multi-task learning layer(DMFS-MT).The former aims at mining long-term spatio-temporal dependencies and local spatio-temporal fluctuation trends in data,respectively,via a new combination of convolutional gated recurrent unit(ConvGRU)and 3-dimensional convolutional neural network(3D-CNN).For the latter,each task is performed for predicting service-specific traffic data based on a fully connected network.On the real-world Telecom Italia dataset,simulation results demonstrate the effectiveness of our proposal through prediction performance measure,spatial pattern comparison and statistical distribution verification.

GUEST EDITORIAL

The landscape of mobile communication networks has been evolving so rapidly.Over the last decades,3G/4G achieved unprecedented success thanks to its advancement in IP for all,and high-speed,mobile and ubiquitous Internet access.Compared with 3G/4G,5G now makes significant advances in terms of connectivity,data rate and latency,which shifts from the conventional people-to-people to the modern people-to-things and things-to-things communication paradigm.

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.

Reconfigurable Intelligent Surfaces for 6G:Nine Fundamental Issues and One Critical Problem

Thanks to the recent advances in metamaterials,Reconfigurable Intelligent Surface(RIS)has emergedas a promising technology for future 6G wireless communications.Benefiting from its high array gain,low cost,and low power consumption,RISs are expected to greatly enlarge signal coverage,improve system capacity,andincrease energy efficiency.In this article,we systematically overview the emerging RIS technology with the focuson its key basics,nine fundamental issues,and one critical problem.Specifically,we first explain the RIS basics,including its working principles,hardware structures,and potential benefits for communications.Based on thesebasics,nine fundamental issues of RISs,such as“What’s the differences between RISs and massive MIMO?”and“Is RIS really intelligent?”,are explicitly addressed to elaborate its technical features,distinguish it from existingtechnologies,and clarify some misunderstandings in the literature.Then,one critical problem of RISs is revealedthat,due to the“multiplicative fading”effect,existing passive RISs can hardly achieve visible performance gains inmany communication scenarios with strong direct links.To address this critical problem,a potential solution calledactive RISs is introduced,and its effectiveness is demonstrated by numerical simulations.

UEs Power Reduction Evolution with Adaptive Mechanism over LTE Wireless Networks

At present, the major drawback for mobile phones is the issue of power consumption. As one of the alternatives to decrease the power consumption of standard, power-hungry location-based services usually require the knowledge of how individual phone features consume power. A typical phone feature is that the applications related to multimedia streaming utilize more power while receiving, processing, and displaying the multimedia contents, thus contributing to the increased power consumption. There is a growing concern that current battery modules have limited capability in fulfilling the long-term energy need for the progress on the mobile phone because of increasing power consumption during multimedia streaming processes. Considering this, in this paper, we provide an offline meaning sleep-mode method to compute the minimum power consumption comparing with the power-on solution to save power by implementing energy rate adaptation(RA) mechanism based on mobile excess energy level purpose to save battery power use. Our simulation results show that our RA method preserves efficient power while achieving better throughput compared with the mechanism without rate adaptation(WRA).

徐州第四代移动通信系统网络规划与实现

移动通信是移动用户之间或移动用户与固定用户之间的通信。随着电子技术的发展,特别是半导体、集成电路和计算机技术的发展,移动通信得到了迅速的发展。随着其应用领域的扩大和对性能要求的提高,促使移动通信在技术上和理论上向更高水平发展。

Dynamic resource allocation schemes for eMBB and URLLC services in 5G wireless networks

The fifth generation(5G)of wireless networks features three core use cases,namely ultra-reliable and low latency communications(URLLC),massive machine type communications(mMTC),and enhanced mobile broadband(eMBB).These use cases co-exist in many practical scenarios and compete for the same set of time and frequency resources,resulting in a natural trade-off in their performance.In this paper,a network supporting both URLLC and eMBB modes of operation is studied.To guarantee the ultra low latency requirement of URLLC,a dynamic resource allocation scheme indicated by a two-dimensional bitmap is proposed.This approach is capable to achieve finer granularity as well as lower false cancellation rate compared to the state-of-the-art methods.A novel power control and indication method is also proposed to dynamically provide different power control parameters to the user equipment(UE),while guaranteeing the reliability requirement of URLLC and minimizing the impact to eMBB.In addition,we devise a dynamic selection mechanism(DSM)to accommodate diverse scenarios,which is empowered with load prediction to become more intelligent.Our extensive system-level simulation results for eMBB-URLLC co-existence scenarios showcase that the perceived throughput of eMBB UEs is increased by 45.3%,while about 13.3% more UEs are enjoying URLLC services with at most 84% transmit power savings compared to the state-of-the-art methods.