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The highly anticipated 5G mmWave technology promises to enable many uplink-oriented, latency-critical applications (LCAs) such as Augmented Reality and Connected Autonomous Vehicles. Nonetheless, recent measurement studies have largely focused on its downlink performance. In thiswork,we perform a systematic study of the uplink performance of commercial 5G mmWave networks across 3 major US cities and 2 mobile operators. Our study makes three contributions. (1) It reveals that 5G mmWave uplink performance is geographically diverse, substantially higher over LTE in terms of bandwidth and latency, but often erratic and suboptimal, which can degrade LCA performance. (2) Our analysis of control messages and PHY-level KPIs shows that the root causes for the suboptimal performance are fundamental to 5G mmWave and cannot be easily fixed via simple tuning of network configurations. (3) We identify various design and deployment optimizations that 5G operators can explore to bring 5G mmWave performance to the level needed to ultimately support the LCAs.
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An In-Depth Measurement Analysis of 5G mmWave PHY Latency and Its Impact on End-to-End Delay
5G aims to offer not only significantly higher throughput than previous generations of cellular networks, but also promises millisecond (ms) and sub-millisecond (ultra-)low latency support at the 5G physical (PHY) layer for future applications. While prior measurement studies have confirmed that commercial 5G deployments can achieve up to several Gigabits per second (Gbps) throughput (especially with the mmWave 5G radio), are they able to deliver on the (sub) millisecond latency promise? With this question in mind, we conducted to our knowledge the first in-depth measurement study of commercial 5G mmWave PHY latency using detailed physical channel events and messages. Through carefully designed experiments and data analytics, we dissect various factors that influence 5G PHY latency of both downlink and uplink data transmissions, and explore their impacts on end-to-end delay. We find that while in the best cases, the 5G (mmWave) PHY-layer is capable of delivering ms/sub-ms latency (with a minimum of 0.09 ms for downlink and 0.76 ms for uplink), these happen rarely. A variety of factors such as channel conditions, re-transmissions, physical layer control and scheduling mechanisms, mobility, and application (edge) server placement can all contribute to increased 5G PHY latency (and thus end-to-end (E2E) delay). Our study provides insights to 5G vendors, carriers as well as application developers/content providers on how to better optimize or mitigate these factors for improved 5G latency performance.
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- Award ID(s):
- 2220286
- PAR ID:
- 10447762
- Date Published:
- Journal Name:
- In Passive and Active Measurement Conference (PAM) 2023.
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Conference Paper:
- https://doi.org/10.1007/978-3-031-28486-1_28
