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ZTE Communications ›› 2019, Vol. 17 ›› Issue (3): 23-30.DOI: 10.12142/ZTECOM.201903005

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  • 收稿日期:2019-07-31 出版日期:2019-09-29 发布日期:2019-12-06

RAN Centric Data Collection for New Radio

GAO Yin, LI Dapeng, HAN Jiren, LIU Zhuang, LIU Yang   

  1. Algorithm Department, ZTE Corporation, Shanghai 201203, China
  • Received:2019-07-31 Online:2019-09-29 Published:2019-12-06
  • About author:GAO Yin (gao.yin1@zte.com.cn) received the master’s degree in circuit and system from Xi’dian University, China in 2005. Since 2005 she has been with the Research Center of ZTE Corporation and engaged in the study of 4G/5G technology. She has authored/co-authored about hundreds of proposals for 3GPP meetings and journal papers in wireless communications and has filed more than 100 patents. She has been elected as the 3GPP RAN3 Vice Chairman from August 2017.|LI Dapeng received the M.S. degree in computer science from University of Electronic Science and Technology of China in 2003. He is currently a senior researcher with ZTE Corporation and mainly focuses on the research and implementation of wireless access network system.|HAN Jiren received the master’s degree in wireless communication systems from University of Sheffield, UK in 2016. He is an advanced research engineer at the Algorithm Department, ZTE Corporation. His research focuses on next generation radio access network.|LIU Zhuang received the master’s degree in computer science from Xi’dian University, China in 2003. He is currently a senior 5G research engineer at the R&D center, ZTE Corporation. His research interests include 5G wireless communications and signal processing.|LIU Yang received the Ph.D. degree in communication and information systems from Beijing University of Posts and Telecommunications, China in 2016. He was a visiting scholar at Department of Electrical and Computer Engineering of North Carolina State University, USA from 2013 to 2015. He is currently an advanced 5G research engineer at the R&D center, ZTE Corporation. His research interests include statistical signal processing, information theory and performance optimization for wireless communication networks.

Abstract:

Self-organizing network (SON) and minimization of driver tests (MDT) are functions designed for Long Term Evolution (LTE) system. SON is designed for network deployment by automatic configuration. MDT is designed for network performance evaluation by automatic signalling procedure. However, these functions do not support new features in new radio (NR) access technology, e.g., multiple radio access technology (RAT)-dual connectivity (MR-DC), central unit-distribute unit (CU-DU) split architecture, beam, etc. Therefore, how to support these features is a challenge for the industry. This paper provides analysis for these problems and provides the summary of SON/MDT functions progress in 3GPP. The analysis includes sub functions such as inter/intra system mobility robustness enhancement, inter/intra system mobility load balance, measurement qualities and mechanism of MDT, energy saving mechanism and procedure, RACH procedure optimization, PCI selection optimization, coverage and capacity optimization, and quality of service (QoS) monitoring mechanism. In addition, this paper also provides an initial thought on artificial intelligence (AI) algorithms applied to SON/MDT functions in NR, so called Smart Grid.

Key words: NR, SON, MDT, data collection