While 5G has offered many opportunities for research, the majority of studies have been conducted with constrained experimental settings or done privately by 5G operators. Even a year after the launch of commercial 5G networks, research over commercial 5G has been limited due to the lack of publicly available tools and datasets. In this paper, we propose 5G Tracker - a crowdsourced platform intended to aid researchers in collecting and leveraging large-scale 5G datasets. This platform includes an Android app that records passive and active measurements tailored to 5G networks and research. We have been using 5G Tracker for over 8 months, during which time we have collected over 4 million data points, consuming over 50 TB of cellular data across multiple 5G carriers in the U.S. Our experience shows that 5G performance is affected by several user-side contextual factors besides location such as user mobility level, orientation, weather, location dynamics (e.g., moving vehicles), and environmental features such as pillars, foliage, and buildings. This is partly because mmWave signals (considered key to mainstream 5G) are known to be highly sensitive to obstructions and user mobility. These observations highlight the need to move towards building context-aware 5G performance prediction models that can provide guidance for decisions at various layers such as preemptive handoff, multi-path scheduling, tower placement, and "5G-aware"application development. Finally, we showcase the utility of our platform by building a first of kind, interactive 5G coverage mapping application as a case study driven by the data we collected, which is publicly available at: https://5gophers.umn.edu.
|Original language||English (US)|
|Title of host publication||Proceedings of the SIGCOMM 2020 Poster and Demo Sessions, SIGCOMM 2020|
|Publisher||Association for Computing Machinery, Inc|
|Number of pages||3|
|State||Published - Aug 10 2020|
|Event||2020 Annual Conference of the ACM Special Interest Group on Data Communication on the Applications, Technologies, Architectures, and Protocols for Computer Communication, SIGCOMM 2020 - Virtual, Online, United States|
Duration: Aug 10 2020 → Aug 14 2020
|Name||Proceedings of the SIGCOMM 2020 Poster and Demo Sessions, SIGCOMM 2020|
|Conference||2020 Annual Conference of the ACM Special Interest Group on Data Communication on the Applications, Technologies, Architectures, and Protocols for Computer Communication, SIGCOMM 2020|
|Period||8/10/20 → 8/14/20|
Bibliographical noteFunding Information:
This research was in part supported by NSF under Grants CNS-1917424, CNS-1903880, CNS-1915122, CNS-1618339, CNS-1617729, CNS-1814322, CNS-1831140, CNS-1836772, and CNS-1901103.
© 2020 Owner/Author.
- 5G tracker