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Balancing Cloud RAN and mobile edge computing

Posted: 10 Mar 2016 ?? ?Print Version ?Bookmark and Share

Keywords:base station? Cloud RAN? Internet-of-Things? 5G? MIMO?

We have seen wireless infrastructure deployment increasingly move to distributed base station architecture over the last couple of years. This architecture centralizes the base band processing pool, sometimes called super Macro, which is capable of feeding a larger number of radios and therefore is more effective for coverage and load balancing. The concept of Cloud RAN takes centralized base station pool all the way into the Cloud co-located with the content or data repositories in the data centre. There are merits in Cloud RAN as it allows use of lower cost compute, leveraging off-the-shelf server chassis for cost effective RAN deployment, load balancing and significant ease in network provisioning. In parallel, Mobile Edge Computing, under the auspices of the ETSI Mobile Edge Computing Industry Standard Group (MEC ISG), is emerging with a concept of placing compute at the edge, co-located with the base band pool, to maintain a local content cache to provide improved services to users.

Caching content locally based on user preferences for lower latency and handling ephemeral data such as location based analytics needs edge computing. These two architecture concepts are proposing to deploy compute at different nodes within the network. On the surface, these two competing architectures appear to be creating opposite pulls, resulting in a dichotomy within the network. A deeper look suggests that a balanced approach to deploying networks could leverage merits of both, thereby transitioning these two competing technologies to complement each other for enabling new services.

More than a decade ago, the concept of distributed base stations emerged with a desire to overcome power loss in sending signals using coaxial cable from traditional base stations located at the foot of towers to antennas mounted on the top of tower. Radio heads were located remotely in close proximity to the antenna on tower top to eliminate power losses. Remote radio heads were connected to base band BTS chassis using fibre. Protocols such as the Common public radio protocol (CPRI) were devised to transport data and synchronise remote radios. In some situations when fibre was not available, microwave or millimeter wave radios were used to transport CPRI payload. This architectural shift raised hopes for operators to mix and match radio and base band chassis from different system vendors to lower costs, improve supply chain, and ease inventory management. Interoperability concerns prevented this from happening, nevertheless it opened the way for tier-1 system vendors to leverage radios from smaller vendors for managing the rapid increase in a variety of radios for different geographies.

Distributed base station architecture has taken roots. This architecture is centralizing the base band processing pool, sometimes called super Macro, which is capable of feeding a larger number of radios and therefore more effective coverage and load balancing. Success of data centre and Cloud computing resulted in the emergence of Cloud RAN concept that extends distributed base station architecture by virtualizing base band pools running on server farms. There are merits in Cloud RAN as it allows use of lower cost compute, leveraging off-the-shelf server chassis for cost effective RAN deployment, load balancing and significant ease in network provisioning. Cloud RAN, when implemented broadly, holds the promise of allowing third party providers to own the network, enabling multiple virtual network providers to concentrate on content and services.

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