5G could open our world up to lightning speed possibilities, or it could clog our world with unmanageable networks.
The two radically different outcomes of implementing 5G networks could depend on two major factors, the degree of machine learning built into the tools that manage the networks, and standardization that will allow multiple networks to talk to one another.
Here is an interview with an expert on the developments of the 5G network, Jakob Hoydis.
|5G won’t just be fast, it’ll do the ML-fuelled self-optimisation thing|
As the ITU wrote, “machine learning applications in communications networking are still very much at their nascent stage of development”.
Nokia Bell Labs’ Jakob Hoydis told an ITU workshop “predicted QoS” is a “very promising application” of machine learning.
There are three working groups in the focus group:
- “Use cases, services, and requirements”, which explains itself;
- “Data formats and machine learning technologies”, which will categorise machine learning algorithms, and define data formats, and mechanisms for privacy and security;
- The third, “Machine Learning-aware network architecture”, will analyse network management architectures as networks increasingly interact with machine learning systems.
Stanczak said expanding auto industry connectivity and massively connected sensors will create massive overhead and “a lot of uncertainty in the network”.
“If we proceed [without machine learning] … the solution wouldn’t be efficient. Machine learning can help increase efficiency and to enable new applications”.
|Read More at The Register|