- This topic has 1 voice and 0 replies.
Viewing 0 reply threads
Viewing 0 reply threads
- You must be logged in to reply to this topic.
› Forums › IoTStack › Announcements(IoTStack) › Saankhya: a self-learning wireless RAN
Tagged: ConnectivityTech_S8, IoTNetwork_H5, Product_A14, Tech_G15, UseCase_G14
#Announcement(IoTStack) #Product [ via IoTForIndiaGroup ]
#Organizer : Saanhya Lab #IsTraining : Springer Link Publication #StartDateTime : 23 March 2019
Springer has published our article on the RAN of the future. If 5g was about “cloudification” and “IT fication” of the core network, 6g will be the ITification of the device. With Deep learning and an entirely radical and new approach to designing Wireless RAN’s , we envision that it would give more power to operators and hopefully make 3gpp truly democratic and out of the clutuches of a few large player ! It would also bring a horses for courses kind of approach to RAN designs.
There is a need to rethink the architecture of RAN from a statically configured RAN to a dynamically self-configuring RAN based on the availability of spectrum (licensed/unlicensed), adjacent channel interference, co-channel interference etc. This will ensure that with configurable wide-band RF and programmable SDR and a Big Data Cloud Compute Server we should be able to operate in any usage scenario like eMBB (enhanced Mobile Broad Band), urLLC (ultra-reliable low latency communication) or mMTC (massive machine type communication) specified in IMT 2020 Vision document.