城市场景5G eMBB网络速率提升研究与应用

在对城市5G eMBB网络遍历测试结果进行聚类分析的基础上,将整个城市网络划分为不同场景,通过数学建模研究不同场景下影响速率的关键要素,并基于关联要素确定每个小区的性能提升重点。通过有针对性的优化,可显著提升5G eMBB网络速率。该研究为城市5G eMBB网络部署后速率快速提升指引了方向,对提升用户感知具有一定指导意义。同时,提出的基于聚类的分析和优化方法也可应用于未来5G SA组网结构下uRLLC和mMTC等场景。     

5G新空口下eMBB与URLLC业务复用技术的研究

5G标准规范体系的演进将致力于解决不同应用场景中的多样化、差异化性能指标,适用频谱资源的缺乏要求5G新空口频段能够同时承载超高速率、超低时延业务。根据3GPP研究计划与进展,5G研究初期以eMBB为主,直到成熟期完善URLLC的标准化。本文主要从物理层设计的角度出发对eMBB与URLLC KPI及相关技术进行了讨论与研究。为了实现不同参数集配置的两种业务模型在同一频段上共存,本文分析了四种应用场景下eMBB与URLLC的两种基本复用方法,旨在减少资源浪费,提升系统的频谱效率。     

5G eMBB场景中SR保护技术应用研究

针对传统第四代移动通信(4G)承载网络只能满足2G、3G和4G无线业务回传承载,而无法满足5G无线回传对承载网络在带宽、时延、切片和可靠性等方面提出的更高需求,更不能满足5G各种业务场景中极高要求的实时保护倒换需求,以及增强型移动宽带(eMBB)场景中业务保护和快速收敛需求,文章提出一种分段路由(SR)隧道技术在5 G...     

5G技术进展及其在车联网应用探讨

5G技术及车联网应用已成为近期行业关注的焦点。文章首先分析5G应用场景及其技术进展,进一步分析了车联网应用的需求、网络指标,最后探讨了车联网应用场景。     

Use cases and scenarios of 5G integrated satellite‐terrestrial networks for enhanced mobile broadband: The SaT5G approach

This paper presents initial results available from the European Commission Horizon 2020 5G Public Private Partnership Phase 2 project “SaT5G” (Satellite and Terrestrial Network for 5G). 1 After describing the concept, objectives, challenges, and research pillars addressed by the SaT5G project, this paper elaborates on the selected use cases and scenarios for satellite communications positioning in the 5G usage scenario of enhanced mobile broadband.     

An Information-Theoretic View of Mixed-Delay Traffic in 5G and 6G

Fifth generation mobile communication systems (5G) have to accommodate both Ultra-Reliable Low-Latency Communication (URLLC) and enhanced Mobile Broadband (eMBB) services. While eMBB applications support high data rates, URLLC services aim at guaranteeing low-latencies and high-reliabilities. eMBB and URLLC services are scheduled on the same frequency band, where the different latency requirements of the communications render their coexistence challenging. In this survey, we review, from an information theoretic perspective, coding schemes that simultaneously accommodate URLLC and eMBB transmissions and show that they outperform traditional scheduling approaches. Various communication scenarios are considered, including point-to-point channels, broadcast channels, interference networks, cellular models, and cloud radio access networks (C-RANs). The main focus is on the set of rate pairs that can simultaneously be achieved for URLLC and eMBB messages, which captures well the tension between the two types of communications. We also discuss finite-blocklength results where the measure of interest is the set of error probability pairs that can simultaneously be achieved in the two communication regimes.     

对中国2020年5G建网困境的分析与建议

2019年5G建网的进展迅速,2020年是5G商用加速起飞的关键一年,由于5G所分配的频谱远高于3G/4G,这导致了5G高昂的建网成本,通信运营商将面临建网资金紧张,运营可能亏损的困境。对2020年5G的投入与收入、建网成本与运营成本做了分析,由于5G是全球高度统一的先进技术标准,按信息经济定律即麦特卡尔夫定律和摩尔定律来分析,5G的长期社会经济效益将非常可观。针对如何降低高昂的建网成本与运营成本,提出了深化共建共享5G网络与高度共享电视黄金频谱二条关键举措,最后对主管部门提出了具体建议,期望5G能早日建成。     

Quality of Service based resource allocation in D2D enabled 5G-CNs with network slicing

With the rapid new advancements in technology, there is an enormous increase in devices and their versatile need for services. Fifth-generation (5G) cellular networks (5G-CNs) with network slicing (NS) have emerged as a necessity for future mobile communication. The available network is partitioned logically into multiple virtual networks to provide an enormous range of users’ specific services. Efficient resource allocation methods are critical to delivering the customers with their required Quality of Service (QoS) priorities. In this work, we have investigated a QoS based resource allocation (RA) scheme considering two types of 5G slices with different service requirements; (1) enhanced Mobile Broadband (eMBB) slice that requires a very high data rate and (2) massive Machine Type Communication (mMTC) slice that requires extremely low latency. We investigated the device-to-device (D2D) enabled 5G-CN model with NS to assign resources to users based on their QoS needs while considering the cellular and D2D user’s data rate requirements. We have proposed a Distributed Algorithm (DA) with edge computation to solve the optimization problem, which is novel as edge routers will solve the problem locally using the augmented Lagrange method. They then send this information to the central server to find the global optimum solution utilizing a consensus algorithm. Simulation analysis proves that this scheme is efficient as it assigns resources based on their QoS requirements. This scheme is excellent in reducing the central load and computational time.