I was part of Cambridge Wireless CWTEC 2018 organising committee where our event 'The inevitable automation of Next Generation Networks' covered variety of topics with AI, 5G, devices, network planning, etc. The presentations are available freely for a limited period here.
One of the thought provoking presentations was by Yue Wang from Samsung R&D. The presentation is embedded below and can be downloaded from Slideshare.End-to-end #AI in telecoms will involve a mix of capabilities on devices, local RAN, core & NFV - @Samsung at #CWTEC— Dean Bubley (@disruptivedean) September 27, 2018
On-device AI can do all sorts of cool stuff eg on power-mgmt pic.twitter.com/SV26fLNnG3
This presentation also brought out some interesting thoughts and discussions:
- While the device-level AI and network-level AI would generally work cooperatively, there is a risk that some vendor may play the system to make their devices perform better than the competitors. Something similar to the signaling storm generated by SCRI (see here).
- If the device-level and network-level AI works constructively, an operator may be able to claim that their network can provide a better battery life for a device. For example iPhone XYZ has 25% better battery life on our network rather than competitors network.
- If the device-level and network-level AI works destructively for any reason then the network can become unstable and the other users may experience issues.
I guess all these enhancements will start slowly and there will be lots of learning in the first few years before we have a stable, mutually beneficial solution.
Related Posts:
- Automating the 5G Core using Machine Learning and Data Analytics
- Telefonica: Big Data, Machine Learning (ML) and Artificial Intelligence (AI) to Connect the Unconnected
- ITU 'Network 2030': Initiative to support Emerging Technologies and Innovation looking beyond 5G advances
- End-to-end Network Slicing in 5G
- 5G New Radio Standards and other Presentations
Really informative sir like always cheers!!
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