Anticipatory QoE Mechanisms in 5G Radio Intelligent Controller
Vidhya R.1, Karthik P.2
1Vidhya R., Department of Telecommunication Engineering, K. S. Institute of Technology, Bangalore, Affiliated to Visvesvaraya Technological Universisty, Belagavi, Karnataka, India.
2Karthik P., Department of E&C, K. S. School of Engineering and Management, Bangalore, Affiliated to Visvesvaraya Technological Universisty, Belagavi, Karnataka, India.
Manuscript received on January 02, 2020. | Revised Manuscript received on January 15, 2020. | Manuscript published on January 30, 2020. | PP: 2509-2513 | Volume-8 Issue-5, January 2020. | Retrieval Number: E6207018520/2020©BEIESP | DOI: 10.35940/ijrte.E6207.018520
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: 3GPP which is working on the 5G specification is also working on the NWDAF (Network Data Analytics Function) which is used for data collection and data analytics in a centralized manner in the 5G Core. ORAN (Open Radio Access Network) is also working on the Radio data collection entities for better handling of the Radio Resource Management which is termed as the Radio Intelligent Controller (RIC). The 5G Network elements and/or the OAM (Operations and Network Management) can decide how to use the data analytics provided by NWDAF and/or the RIC to improve the overall system performance. In this paper we show how to develop anticipatory QoE mechanisms by using the data available at the RIC and the NWDAF. We show that anticipatory AI functionality will help address QoE in a mobile video streaming use case.
Keywords: 5G, Mobile Video Streaming, QoE, NWDAF
Scope of the Article: 5G Communication.