Abstract
By aggregating multiple channels, Carrier Aggregation (CA) is an important technology for boosting cellular network bandwidth. Given diverse radio bands made available in 5G networks, CA plays a particularly critical role in achieving the goal of multi-Gbps throughput performance. In this paper, we carry out a timely comprehensive measurement study of CA deployment in commercial 5G networks (as well as 4G networks). We identify the key factors that influence whether CA is deployed and when, as well as which band combinations are used. Thus, we reveal the challenges posed by CA in 5G performance analysis and prediction as well as their implications in application quality-of-experience (QoE). We argue for and develop a novel CA-aware deep learning framework, dubbed Prism5G, which explicitly accounts for the complexity introduced by CA to more effectively predict 5G network throughput performance. Through extensive evaluations, we demonstrate the superiority of Prism5G over existing throughput prediction algorithms. Prism5G improves 5G throughput prediction accuracy by over 14% on average and a maximum of 22%. Using two use cases as examples, we further illustrate how Prism5G can aid applications in optimizing QoE performance.
Original language | English (US) |
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Title of host publication | ACM SIGCOMM 2024 - Proceedings of the 2024 ACM SIGCOMM 2024 Conference |
Publisher | Association for Computing Machinery, Inc |
Pages | 340-357 |
Number of pages | 18 |
ISBN (Electronic) | 9798400706141 |
State | Published - Aug 4 2024 |
Event | 2024 ACM SIGCOMM Conference, ACM SIGCOMM 2024 - Sydney, Australia Duration: Aug 4 2024 → Aug 8 2024 |
Publication series
Name | ACM SIGCOMM 2024 - Proceedings of the 2024 ACM SIGCOMM 2024 Conference |
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Conference
Conference | 2024 ACM SIGCOMM Conference, ACM SIGCOMM 2024 |
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Country/Territory | Australia |
City | Sydney |
Period | 8/4/24 → 8/8/24 |
Bibliographical note
Publisher Copyright:© 2024 Copyright is held by the owner/author(s). Publication rights licensed to ACM.
Keywords
- 4G
- 5G
- carrier aggregation
- deep learning
- mobile network throughput prediction
- network measurement