Keynote 2: How future networks will become proactive? Machine learning to solve a pertinent engineering challenge
Abstract/Description
The cellular network have long been configured and optimised reactively by identifying events and triggers and readjusting the operation of the cellular system. Our research is paving the way to make a step change by introducing proactive techniques to pre-emptively trigger actions that will make the networks more agile in adapting to changing demands of service and quality of experience. With the advent of ultra-dense deployment of networks, we need to use such mechanisms to schedule multi-level sleep modes of cells, mobility management as well as joint RAN-backhaul optimisation from efficiency perspective. As a use case, we will focus on the energy efficiency aspect covering the fundamental framework for the evaluation of energy efficiency and the state of the art as well as futuristic approaches to achieve energy efficiency.
Location
JS Auditorium
Session Theme
Keynote Session II
Session Type
Keynote Speech
Start Date
16-11-2019 10:50 AM
End Date
16-11-2019 11:30 AM
Recommended Citation
Imran, D. (2019). Keynote 2: How future networks will become proactive? Machine learning to solve a pertinent engineering challenge. International Conference on Information and Communication Technologies. Retrieved from https://ir.iba.edu.pk/icict/2019/2019/3
COinS
Keynote 2: How future networks will become proactive? Machine learning to solve a pertinent engineering challenge
JS Auditorium
The cellular network have long been configured and optimised reactively by identifying events and triggers and readjusting the operation of the cellular system. Our research is paving the way to make a step change by introducing proactive techniques to pre-emptively trigger actions that will make the networks more agile in adapting to changing demands of service and quality of experience. With the advent of ultra-dense deployment of networks, we need to use such mechanisms to schedule multi-level sleep modes of cells, mobility management as well as joint RAN-backhaul optimisation from efficiency perspective. As a use case, we will focus on the energy efficiency aspect covering the fundamental framework for the evaluation of energy efficiency and the state of the art as well as futuristic approaches to achieve energy efficiency.
