Recently , Deep-learning and AI techniques have received more attention as a key enabler for future 5G and beyond wireless networks.
Do you have any ideas about what 5G problems this technology can be used to solve them.
At present strong-AI is not yet invented, in fact it may be 10-years before the theory is fully developed so that practical applications in technology are possible. Consequently I don't see any possible applications to improve 5G, currently, and will likely be at least 10-years in future. By that time, 5G will be obsolete, and we will have moved to more advanced systems.
At present strong-AI is not yet invented, in fact it may be 10-years before the theory is fully developed so that practical applications in technology are possible. Consequently I don't see any possible applications to improve 5G, currently, and will likely be at least 10-years in future. By that time, 5G will be obsolete, and we will have moved to more advanced systems.
Dear Kahled,
R. Poznanski has just made a comment pertinent to your question on another thread; I recommend that you follow him to keep-up with the cutting-edge of the research/theory developments in strong-AI:
https://www.researchgate.net/post/Can_we_mathematically_model_consciousness#view=5c6b712136d235bec050340e
Regards,
Bob Skiles
PS - perhaps if you invite him (via message) he may be kind enough to provide a comment /answer on your question/thread, here.
Deep learning can assist a wide range of applications in mobile networks. Applications vary based on whether the data is collected by mobile device sensors or mobile network infrastructure.
To name a few:
1) Network state prediction (e.g., cellular traffic prediction, network traffic classification, channel state information prediction, QoE prediction)
2) Mobility management (e.g., mobile user trajectory prediction, city-wide movement patterns of users/vehicles)
3) User localization based services (e.g., mobile location estimation based on channel state information)
4) Network management (e.g., Cellular random access optimization, handover optimization, IoT load balancing, dynamic orchestration of networks (VNF scaling, VNF migration), networking slicing configuration prediction)
Dear Bob Skiles
Thank you for your answer and recommendation. Now I am following @ Roman R Poznanski in order to keep-up with the state of the art.
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