5G Fronthaul Handbook – Viavi Solutions – Dec 2019

5G Fronthaul Handbook by Viavi Solutions.

A guide to understanding the impact of 5G on transport networks and key test considerations for ensuring reliable performance and high quality of service.

5G Fronthaul Evolution: The Beginning.

5G technology is touted as an innovation platform that will enhance our connected world. To deliver on this promise, 5G will demand the network supporting it to be as flexible as the services running on it. The following high-level 5G uses cases are well understood and documented by the wireless industry:

• Enhanced Mobile Broadband (eMBB) providing greater data-bandwidth services with peak data rates of 10 Gbps and beyond. This data rate will enable new use cases such as augmented reality/ virtual reality or ultra-high density (UltraHD) applications.
• Ultra-Reliable Low Latency Communications (URLLC) providing ultra-reliable capabilities with availabilities in the range of 99.9999%, and extremely low latency features in millisecond range. Vehicle-to-vehicle communication over 5G networks is one prominent use case for this category.
• Massive Machine Type Communication (mMTC) supporting extremely large numbers of devices in the range of hundreds of thousands per square kilometer. Essential for this application class are battery lives up to ten years.

Importance of key capabilities in different usage scenarios (from ITU IMT Vision)

The big challenge is how to support these use cases on the same network. Much of the trade buzz to date has been centered on 5G-NR (new radio), virtualized core, and mm-Wave spectrum. Receiving far less attention, but equally important as the new radio interface, is the evolution of the transport network connecting 5G nodes that enable the key 5G use cases –simultaneously. In the 2019 Heavy Reading survey Operator Strategies for 5G Transport, Heavy Reading reported, “the industry has recognized that this transport infrastructure must be put in place before 5G applications can be rolled out in volume”.

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