发帖
雷达卡
摘要翻译：
云无线接入网（C-RAN）为蜂窝网络的部署、管理和演进提供了一种革命性的方法。此外，软件定义无线电(SDR)和网络技术的进步，使得通过云交付软件定义的一切成为可能。资源将通过抽象、虚拟化和整合技术进行池化和动态分配；过程将使用通用的应用程序编程接口实现自动化；网络功能和服务将通过编排器以编程方式提供。OOCRAN是一个基于ETSI提出的NFV MANO体系结构的软件框架。它为整个无线基础设施提供了一个编排层，包括硬件、软件、频谱、前端和回程。OOCRAN通过合并无线电通信层及其管理依赖关系来扩展现有的NFV管理框架。然后，无线基础设施提供商可以动态地向无线服务提供商提供虚拟化无线网络。测试床的物理基础设施是围绕一个计算集群构建的，该集群执行开源SDR库，并连接到基于SDR的远程无线电头。我们演示了OOCRAN的操作，并讨论了动态LTE小蜂窝网络部署的时间含义。
---
英文标题：
《Open Orchestration Cloud Radio Access Network (OOCRAN) Testbed》
---
作者：
Marti Floriach-Pigem, Guillem Xercavins-Torregrosa, Vuk Marojevic,
Antoni Gelonch-Bosch
---
最新提交年份：
2017
---
分类信息：
一级分类：Computer Science 计算机科学
二级分类：Networking and Internet Architecture 网络和因特网体系结构
分类描述：Covers all aspects of computer communication networks, including network architecture and design, network protocols, and internetwork standards (like TCP/IP). Also includes topics, such as web caching, that are directly relevant to Internet architecture and performance. Roughly includes all of ACM Subject Class C.2 except C.2.4, which is more likely to have Distributed, Parallel, and Cluster Computing as the primary subject area.
涵盖计算机通信网络的所有方面，包括网络体系结构和设计、网络协议和网络间标准（如TCP/IP）。还包括与Internet体系结构和性能直接相关的主题，如web缓存。大致包括除C.2.4以外的所有ACM主题类C.2，后者更有可能将分布式、并行和集群计算作为主要主题领域。
--
一级分类：Electrical Engineering and Systems Science 电气工程与系统科学
二级分类：Signal Processing 信号处理
分类描述：Theory, algorithms, performance analysis and applications of signal and data analysis, including physical modeling, processing, detection and parameter estimation, learning, mining, retrieval, and information extraction. The term "signal" includes speech, audio, sonar, radar, geophysical, physiological, (bio-) medical, image, video, and multimodal natural and man-made signals, including communication signals and data. Topics of interest include: statistical signal processing, spectral estimation and system identification; filter design, adaptive filtering / stochastic learning; (compressive) sampling, sensing, and transform-domain methods including fast algorithms; signal processing for machine learning and machine learning for signal processing applications; in-network and graph signal processing; convex and nonconvex optimization methods for signal processing applications; radar, sonar, and sensor array beamforming and direction finding; communications signal processing; low power, multi-core and system-on-chip signal processing; sensing, communication, analysis and optimization for cyber-physical systems such as power grids and the Internet of Things.
信号和数据分析的理论、算法、性能分析和应用，包括物理建模、处理、检测和参数估计、学习、挖掘、检索和信息提取。“信号”一词包括语音、音频、声纳、雷达、地球物理、生理、（生物）医学、图像、视频和多模态自然和人为信号，包括通信信号和数据。感兴趣的主题包括：统计信号处理、谱估计和系统辨识；滤波器设计；自适应滤波/随机学习；（压缩）采样、传感和变换域方法，包括快速算法；用于机器学习的信号处理和用于信号处理应用的机器学习；网络与图形信号处理；信号处理中的凸和非凸优化方法；雷达、声纳和传感器阵列波束形成和测向；通信信号处理；低功耗、多核、片上系统信号处理；信息物理系统的传感、通信、分析和优化，如电网和物联网。
--
---
英文摘要：
The Cloud radio access network (C-RAN) offers a revolutionary approach to cellular network deployment, management and evolution. Advances in software-defined radio (SDR) and networking technology, moreover, enable delivering software-defined everything through the Cloud. Resources will be pooled and dynamically allocated leveraging abstraction, virtualization, and consolidation techniques; processes will be automated using common application programming interfaces; and network functions and services will be programmatically provided through an orchestrator. OOCRAN, oocran.dynu.com, is a software framework that is based on the NFV MANO architecture proposed by ETSI. It provides an orchestration layer for the entire wireless infrastructure, including hardware, software, spectrum, fronthaul and backhaul. OOCRAN extends existing NFV management frameworks by incorporating the radio communications layers and their management dependencies. The wireless infrastructure provider can then dynamically provision virtualized wireless networks to wireless service providers. The testbed's physical infrastructure is built around a computing cluster that executes open-source SDR libraries and connects to SDR-based remote radio heads. We demonstrate the operation of OOCRAN and discuss the temporal implications of dynamic LTE small cell network deployments.
---
PDF链接：
https://arxiv.org/pdf/1712.03328
京公网安备 11010802022788号
