Motivated by the rapid deployment of 5G, we carry out an in-depth measurement study of the performance, power consumption, and application quality-of-experience (QoE) of commercial 5G networks in the wild. We examine different 5G carriers, deployment schemes (Non-Standalone, NSA vs. Standalone, SA), radio bands (mmWave and sub 6-GHz), protocol configurations (_e.g._ Radio Resource Control state transitions), mobility patterns (stationary, walking, driving), client devices (_i.e._ User Equipment), and upper-layer applications (file download, video streaming, and web browsing). Our findings reveal key characteristics of commercial 5G in terms of throughput, latency, handover behaviors, radio state transitions, and radio power consumption under the above diverse scenarios, with detailed comparisons to 4G/LTE networks. Furthermore, our study provides key insights into how upper-layer applications should best utilize 5G by balancing the critical tradeoff between performance and energy consumption, as well as by taking into account the availability of both network and computation resources. We have released the datasets and tools of our study at https://github.com/SIGCOMM21-5G/artifact.
|Original language||English (US)|
|Title of host publication||SIGCOMM 2021 - Proceedings of the ACM SIGCOMM 2021 Conference|
|Publisher||Association for Computing Machinery, Inc|
|Number of pages||16|
|State||Published - Aug 9 2021|
|Event||2021 Annual Conference of the ACM Special Interest Group on Data Communication on the Applications, SIGCOMM 2021 - Virtual, Online, United States|
Duration: Aug 23 2021 → Aug 27 2021
|Name||SIGCOMM 2021 - Proceedings of the ACM SIGCOMM 2021 Conference|
|Conference||2021 Annual Conference of the ACM Special Interest Group on Data Communication on the Applications, SIGCOMM 2021|
|Period||8/23/21 → 8/27/21|
Bibliographical noteFunding Information:
We thank our shepherd Mythili Vutukuru and the anonymous reviewers for their suggestions and feedback. We also thank Art Brisebois and Gyan Ranjan from Ericsson (US) for providing deeper insights on our measurement study. This research was in part supported by NSF under Grants CNS-1814322, CNS-1836722, CNS-1901103, CNS-1915122, CNS-1903880, CNS-1930041, CNS-1544678, and CCF-1628991.
© 2021 ACM.
- energy efficiency
- network measurement
- power characteristics
- power model
- video streaming