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.

Mathew, S., Oliosi, E., Davoli, L., Strozzi, N., Notari, A., Ferrari, G. (2024). CSI-RSRP-Based Unnecessary Handover Mitigation Through Linear Regression in Dynamic 5G NR Environments. IEEE ACCESS, 12, 121808-121821 [10.1109/access.2024.3451483].

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

Oliosi, Eleonora;Ferrari, Gianluigi
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.
2024
Mathew, S., Oliosi, E., Davoli, L., Strozzi, N., Notari, A., Ferrari, G. (2024). CSI-RSRP-Based Unnecessary Handover Mitigation Through Linear Regression in Dynamic 5G NR Environments. IEEE ACCESS, 12, 121808-121821 [10.1109/access.2024.3451483].
Mathew, Sunil; Oliosi, Eleonora; Davoli, Luca; Strozzi, Nicolò; Notari, Andrea; Ferrari, Gianluigi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/1004634
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