Name
Abstract | ||
|---|---|---|
ABSTRACTThe 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 this work, 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. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1145/3538394.3546042 | ACM SIGCOMM |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 9 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Moinak Ghoshal | 1 | 0 | 1.69 |
| Z. Jonny Kong | 2 | 0 | 1.35 |
| Qiang Xu | 3 | 6 | 7.23 |
| Zixiao Lu | 4 | 0 | 0.34 |
| Shivang Aggarwal | 5 | 15 | 5.68 |
| Imran Khan | 6 | 0 | 0.34 |
| Yuanjie Li | 7 | 243 | 38.95 |
| Y. Charlie Hu | 8 | 3357 | 181.75 |
| Dimitrios Koutsonikolas | 9 | 0 | 2.03 |