Abstract
The emerging 5G services offer numerous new opportunities for networked applications. In this study, we seek to answer two key questions: i) is the throughput of mmWave 5G predictable, and ii) can we build "good"machine learning models for 5G throughput prediction? To this end, we conduct a measurement study of commercial mmWave 5G services in a major U.S. city, focusing on the throughput as perceived by applications running on user equipment (UE). Through extensive experiments and statistical analysis, we identify key UE-side factors that affect 5G performance and quantify to what extent the 5G throughput can be predicted. We then propose Lumos5G - a composable machine learning (ML) framework that judiciously considers features and their combinations, and apply state-of-the-art ML techniques for making context-aware 5G throughput predictions. We demonstrate that our framework is able to achieve 1.37X to 4.84X reduction in prediction error compared to existing models. Our work can be viewed as a feasibility study for building what we envisage as a dynamic 5G throughput map (akin to Google traffic map). We believe this approach provides opportunities and challenges in building future 5G-aware apps.
Original language | English (US) |
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Title of host publication | IMC 2020 - Proceedings of the 2020 ACM Internet Measurement Conference |
Publisher | Association for Computing Machinery |
Pages | 176-193 |
Number of pages | 18 |
ISBN (Electronic) | 9781450381383 |
DOIs | |
State | Published - Oct 27 2020 |
Event | 20th ACM Internet Measurement Conference, IMC 2020 - Virtual, Online, United States Duration: Oct 27 2020 → Oct 29 2020 |
Publication series
Name | Proceedings of the ACM SIGCOMM Internet Measurement Conference, IMC |
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Conference
Conference | 20th ACM Internet Measurement Conference, IMC 2020 |
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Country/Territory | United States |
City | Virtual, Online |
Period | 10/27/20 → 10/29/20 |
Bibliographical note
Publisher Copyright:© 2020 ACM.
Keywords
- 5G
- Lumos5G
- bandwidth estimation
- deep learning
- machine learning
- mmWave
- prediction
- throughput prediction