Measurement-based Optimization of Cell Selection in NB-IoT Networks

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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Author(s)

  • Xiangmao Chang
  • Jun Zhan
  • Guoliang Xing
  • Bing Chen
  • Lu Zhou

Related Research Unit(s)

Detail(s)

Original languageEnglish
Article number65
Journal / PublicationACM Transactions on Sensor Networks
Volume18
Issue number4
Online published16 Jun 2022
Publication statusPublished - Nov 2022

Abstract

Narrowband-Internet of Things (NB-IoT) is an emerging cellular communication technology designed for low power wide area applications. Cell selection determines the channel of user device and hence is an important issue in cellular networks. In this paper, we take the first attempt to examine and optimize the the cell selection in NB-IoT networks by field measurement. We conduct measurements at 30 different locations which involve 5 typical application scenarios of NB-IoT. Two kinds of NB-IoT modules and two network operators are also involved in the measurements. We find four potential issues on the cell selection of the User Equipment (UE) through the measurements. We propose an adaptive cell selection approach to optimize the cell selection of UE. The simulation test based on real-world measurement data shows that the cell selected by the adaptive approach can improve the coverage level and reduce the power consumption for UE.

Bibliographic Note

Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).

Citation Format(s)

Measurement-based Optimization of Cell Selection in NB-IoT Networks. / Chang, Xiangmao; Zhan, Jun; Xing, Guoliang et al.
In: ACM Transactions on Sensor Networks, Vol. 18, No. 4, 65, 11.2022.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review