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CSI-RSRP-Based Unnecessary Handover Mitigation Through Linear Regression in Dynamic 5G NR Environments

Authors :
Sunil Mathew
Eleonora Oliosi
Luca Davoli
Nicolo Strozzi
Andrea Notari
Gianluigi Ferrari
Source :
IEEE Access, Vol 12, Pp 121808-121821 (2024)
Publication Year :
2024
Publisher :
IEEE, 2024.

Abstract

5G New Radio (NR), introduced in 2019 in the 3rd Generation Partnership Project (3GPP) Release 15, has become the global radio standard for 5G networks. Because of the presence of an increasing number of available 5G gNodeBs (gNBs), HandOver (HO) management is crucial, especially in terms of Quality of Service (QoS) and Quality of Experience (QoE) perceived by a User Equipment (UE). Unnecessary HandOvers (UHOs) cause latency peaks (on the order hundreds of milliseconds) and multiple throughput drops in 5G communications. In this paper, we first carry out an experimental campaign to investigate the behaviour of latency and throughput in correspondence to UHOs. Then, on the basis of a Matlab-based 5G NR DownLink (DL) transmission simulator, we propose an innovative linear regression-based algorithm to avoid UHOs, which relies on Channel State Information-Reference Signal Received Power (CSI-RSRP) measurements.

Details

Language :
English
ISSN :
21693536
Volume :
12
Database :
Directory of Open Access Journals
Journal :
IEEE Access
Publication Type :
Academic Journal
Accession number :
edsdoj.0ff9098dd1a94fb0b66920409851d25d
Document Type :
article
Full Text :
https://doi.org/10.1109/ACCESS.2024.3451483