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Centralized RAN or C-RAN is an architectural shift in RAN (Radio Access Network) design, where the bulk of baseband processing is centralized and aggregated for a large number of distributed radio nodes. In comparison to standalone clusters of base stations, C-RAN provides significant performance and economic benefits such as baseband pooling, enhanced coordination between cells, virtualization, network extensibility, smaller deployment footprint and reduced power consumption. Although Japan and South Korea continue to spearhead commercial C-RAN investments, interest is also growing in other parts of the world. Mobile operators such as China Mobile, Orange, Verizon and Sprint are already investing in the technology. SNS Research estimates that global investments on C-RAN architecture networks will reach over $7 Billion by the end of 2016. The market is further expected to grow at a CAGR of nearly 20% between 2016 and 2020. These investments will include spending on RRHs (Remote Radio Heads), BBUs (Baseband Units) and fronthaul transport networking gear. For more information or any query mail at sales@wiseguyreports.com The “C-RAN (Centralized Radio Access Network) Ecosystem: 2016 - 2030 – Opportunities, Challenges, Strategies & Forecasts” report presents an in-depth assessment of the C-RAN ecosystem including enabling technologies, key trends, market drivers, challenges, standardization, regulatory landscape, deployment models, operator case studies, opportunities, future roadmap, value chain, ecosystem player profiles and strategies. The report also presents forecasts for C-RAN infrastructure investments from 2016 till 2030. The forecasts cover 3 individual submarkets and 6 regions. The report comes with an associated Excel datasheet suite covering quantitative data from all numeric forecasts presented in the report. List of Companies Mentioned 3GPP (3rd Generation Partnership Project) 6WIND Absolute Analysis Accelink Technologies ADLINK Technology ADTRAN ADVA Optical Networking Advantech Airspan Networks Airvana Alcatel-Lucent Altera Corporation Altiostar Networks Amarisoft América Móvil Group Anite Anritsu Corporation Aquantia ARM Holdings Artemis Networks Artesyn Embedded Technologies Artiza Networks ASOCS ASTRI (Hong Kong Applied Science and Technology Research Institute) Avago Technologies Aviat Networks Axxcelera Broadband Wireless (Moseley Associates) BLiNQ Networks Blu Wireless Technology BluWan BridgeWave Communications Broadcom Corporation Cambium Networks Cavium CBNL (Cambridge Broadband Networks Ltd.) CCS (Cambridge Communication Systems) Ceragon China Mobile China Telecom Ciena Corporation Cisco Systems Cobham Wireless Coherent Logix Comcores ApS CommAgility 2 Chapter 2: An Overview of C-RAN 2.1 What is C-RAN? 2.1.1 Decoupling the Base Station 2.1.2 Brief History 2.2 Competing RAN Architectures 2.2.1 Traditional Macrocells 2.2.2 Small Cells 2.2.3 DAS (Distributed Antenna Systems) 2.3 Key Architectural Components for C-RAN 2.3.1 RRH (Remote Radio Head) 2.3.2 BBU (Baseband Unit) 2.3.3 Fronthaul 2.4 Baseband Functional Split Approaches 2.4.1 Fully Centralized Baseband Processing 2.4.2 Partially Centralized: RRH with L1 & L2 Baseband Capabilities 2.5 Fronthaul Interface Options 2.5.1 CPRI (Common Public Radio Interface) 2.5.2 OBSAI (Open Base Station Architecture Initiative) 2.5.3 ORI (Open Radio Interface) 2.5.4 Ethernet 2.6 Cloud RAN: Virtualizing C-RAN 2.6.1 Leveraging Commodity Technologies 2.6.2 Moving RAN to the Cloud 2.7 Market Growth Drivers 2.7.1 Capacity & Coverage Improvement: Addressing the Mobile Data Traffic Tsunami 2.7.2 Towards Greener RANs: Cost Efficiency & Energy Savings 2.7.3 Agile & Flexible Network Architecture 2.7.4 Enhanced Support for LTE-Advanced Features 2.7.5 The Benefits of Virtualization 2.7.6 Impact of 5G Rollouts 2.8 Market Barriers 2.8.1 Fronthaul Investments 2.8.2 Virtualization Challenges 2.8.3 Migration from Legacy Architectures 3 Chapter 3: Standardization & Regulatory Initiatives 3.1 3GPP (3rd Generation Partnership Project) 3.2 ETSI (European Telecommunications Standards Institute) 3.2.1 ORI for Fronthaul 3.2.2 NFV (Network Functions Virtualization) for Cloud RAN 3.2.3 MEC (Mobile Edge Computing) 3.3 NGMN (Next Generation Mobile Networks) Alliance 3.3.1 P-CRAN (Project Centralized RAN) 3.4 Small Cell Forum 3.4.1 Release 5.1: Small Cell Virtualization 3.5 MEF (Metro Ethernet Forum) 3.5.1 Ethernet Transport 3.6 IEEE (Institute of Electrical and Electronics Engineers) 3.6.1 IEEE 802.1CM: Time-Sensitive Networking for Fronthaul 3.6.2 IEEE P1904.3: Standard for RoE (Radio over Ethernet) Encapsulations and Mappings 3.6.3 Other Standards & Work Groups 3.7 ITU (International Telecommunications Union) 3.7.1 Focus Group on IMT-2020 For more information or any query mail at sales@wiseguyreports.com ABOUT US: Wise Guy Reports is part of the Wise Guy Consultants Pvt. Ltd. and offers premium progressive statistical surveying, market research reports, analysis & forecast data for industries and governments around the globe. Wise Guy Reports features an exhaustive list of market research reports from hundreds of publishers worldwide. We boast a database spanning virtually every market category and an even more comprehensive collection of market research reports under these categories and sub-categories. For more information, please visit https://www.wiseguyreports.com


Bercovich D.,Ceragon | Contreras L.M.,Telefonica | Haddad Y.,Jerusalem College of Technology | Adam A.,Ceragon | Bernardos C.J.,Charles III University of Madrid
Mobile Networks and Applications | Year: 2015

Traditionally microwave backhaul has been configured and operated in a static manner by means of vendor specific management systems. This mode of operation will be difficult to adapt to the new challenges originated by 5G networks. New mechanisms for adaptation and flexibility are required also in this network segment. The usage of a signaled control plane solution (based on OpenFlow) will facilitate the operation and will provide means for automation of actions on the wireless transport network segment. In addition to that, a standard control plane helps to reach the multi-vendor approach reducing complexity and variety of current per-vendor operation. This paper presents the motivation for the introduction of programmability concepts in wireless transport networks and illustrate the applicability of such control plane with two relevant use cases for dynamically controlling wireless transport nodes in 5G networks. Extensions to OpenFlow protocol are also introduced for building Software Defined Wireless Transport Networks (SDWTNs). © 2015 Springer Science+Business Media New York


Miranda J.F.,Norwegian University of Science and Technology | Gjertsen K.M.,Ceragon | Olavsbraten M.,Norwegian University of Science and Technology
RWW 2012 - Proceedings: 2012 IEEE Topical Conference on Power Amplifiers for Wireless and Radio Applications, PAWR 2012 | Year: 2012

Driving the gate and drain biases as a function of the input power significantly enhances the efficiency of class-A and -AB amplifiers. These functions are described as low-order polynomials in order to limit the bias bandwidth, especially at the drain. This work formulates the optimization of the bias polynomial coefficients as a constrained optimization problem, describing in detail the formulation of the constraints, the structure of the cost function, as well as a relevant linearity measure. Using the random search algorithm within the field of stochastic search optimization, a set of solutions was obtained yielding power added efficiency nearly as high as 50 %, while the linearity was comparable to that of a class-A amplifier. © 2012 IEEE.

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