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  4. > The C-RAN (Centralized Radio Access Network) Ecosystem: 2016 – 2030 – Opportunities, Challenges, Strategies & Forecasts

The C-RAN (Centralized Radio Access Network) Ecosystem: 2016 – 2030 – Opportunities, Challenges, Strategies & Forecasts

  • January 2016
  • -
  • SNS Telecom
  • -
  • 250 pages

Summary

Table of Contents

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.

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.

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