@inproceedings{f4ec9e0ce073479cb0078028eb797dc6,
title = "Prediction and exposure of delays from a base station perspective in 5G and beyond networks",
abstract = "The inherent flexibility of 5G networks come with a high degree of configuration and management complexity. This makes the performance outcome for UEs, more than ever, dependent on intricate configurations and interplay between algorithms at various network components. In this paper, we take initial steps towards a performance exposure system at the base station using a data-driven approach for predicting performance violations in terms of RTT, as observed by the UE, in a 5G mmWave network. We present ML models to predict RTT using low-level and high-frequency base station metrics from a 5G mmWave testbed based on commercially available equipment. Predicting UE performance from a base station perspective, and exposing this knowledge, is valuable for applications to proactively address performance violations. We also compare several methods for feature reduction, which have a significant impact on monitoring load. We demonstrate our model's ability to identify RTT violations, paving the way for network providers towards an intelligent performance exposure system.",
keywords = "5G, delay prediction, machine learning, measurements",
author = "Akhila Rao and William T{\"a}rneberg and Emma Fitzgerald and Lorenzo Corneo and Aleksandr Zavodovski and Omkar Rai and Sixten Johansson and Viktor Berggren and Hassam Riaz and Caner Kilinc and Andreas Johnsson",
year = "2022",
month = aug,
day = "22",
doi = "10.1145/3538394.3546039",
language = "English",
series = "5G-MeMU 2022 - Proceedings of the ACM SIGCOMM 2022 Workshop on 5G and Beyond Network Measurements, Modeling, and Use Cases - Part of SIGCOMM 2022",
publisher = "Association for Computing Machinery (ACM)",
pages = "8--14",
booktitle = "5G-MeMU 2022 - Proceedings of the ACM SIGCOMM 2022 Workshop on 5G and Beyond Network Measurements, Modeling, and Use Cases - Part of SIGCOMM 2022",
address = "United States",
note = "2022 ACM SIGCOMM Workshop on 5G and Beyond Network Measurements, Modeling, and Use Cases, 5G-MeMU 2022, co-located with ACM SIGCOMM 2022 ; Conference date: 22-08-2022",
}