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Will it be possible to successfully operate 5G networks without analytics?

Data analytics is often called the ‘key to unlocking 5G’, but what is the importance of data when delivering this next generation architecture?

Enhanced mobile broadband


To a consumer, 5G simply means faster speeds and greater bandwidth. But from an industry perspective, analytics will be harnessed to segment audiences by the applications they use to deliver enhanced experiences.

This form of virtual network architecture is called network slicing and will play a huge role as SDN and NFV rolls out commercially.

A best use case is a self-driving car that requires low latency but not necessarily a high throughput, which is the opposite for the kids watching Netflix in the back. Network analytics will be able to determine how the network should be virtually sliced, to provide the best experience for the customer and least impact on the bandwidth.

IoT analytics


With the advent of driving cars, virtual assistants and inexpensive sensors, Gartner have predicted connected IoT devices will reach 20.8 billion by 2020, the same time 5G is set to be commercially rolled out.

The role of 5G in machine to machine (M2M) communication will prove pivotal as many of these devices will be on the move and will require a low latency connection. Edge computing, hosted by telco networks will allow for this moving data to be captured and returned to the machine in real time.

Heavy Reading senior analyst Jim Hodges is especially sceptical about "monetization of NFV, the cloud and security demand real-time analytics… Will it be possible to [successfully] operate 5G networks without analytics? I don't think it will be possible. Our industry hasn't tied real-time analytics and big data to the cloud, NFV, security and 5G, but we need to."

AI & MI


Apple never gives telecos the memo that they are about to live stream an iPhone launch event. And when consumers increasingly tune in to watch the event live in high definition on their 5G connection, it will be AI that will react accordingly.

"The resources are always going to be limited, the bandwidth is going to be limited," says Mazin Gilbert, AVP of Intelligent Services at AT&T Labs. "The ability to smartly and intelligently figure out how to move traffic from one place to the other is a big challenge. And there is tremendous room for AI and machine learning to do a better and a smarter job as we go to 5G, and anticipate traffic, not just react."

Network issues involving congestion, equipment failure and traffic spikes will be automatically mitigated by machine learning using data analytics as its fuel. With so many network ‘edges’ in place and so many more devices, humans cannot be expected to manually keep track of this unpredictable and sporadic traffic.

Session


Presentation

Next Generation Architecture - The Elevated Role of Analytics with the Introduction of 5G

  • Efficiently rolling out 5G using big data analytics
  • New business cases - analysing valuable granular data
  • Making analytics key to delivering 5G
  • Preparing for network complexity and interconnectedness
  • Equipping data centres with the capability to monitor vast amounts of traffic data