Name
Title | ||
|---|---|---|
Effect of Spatial, Temporal and Network Features on Uplink and Downlink Throughput Prediction |
Abstract | ||
|---|---|---|
Recently, there have been many attempts to apply Machine Learning (ML)-based prediction mechanisms In wireless networks. One open question is how reliable such predictions can be, and how well ML models can learn from the radio environment. In this paper, we present initial results on Quality of Service (QoS) prediction using the example of throughput prediction. We focus on suggesting new sets of... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/5GWF52925.2021.00080 | 2021 IEEE 4th 5G World Forum (5GWF) |
Keywords | DocType | ISBN |
Artificial Intelligence,Machine Learning,Quality of Service,Throughput Prediction,High Mobility | Conference | 978-1-6654-4308-1 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
12 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alexandros Palaios | 1 | 0 | 2.03 |
| Christian Vielhaus | 2 | 0 | 0.34 |
| Daniel F. Külzer | 3 | 0 | 0.34 |
| Philipp Geuer | 4 | 0 | 1.69 |
| Raja Sattiraju | 5 | 19 | 5.29 |
| Jochen Fink | 6 | 0 | 2.37 |
| Martin Kasparick | 7 | 55 | 12.55 |
| Cara Watermann | 8 | 0 | 0.34 |
| Gerhard Fettweis | 9 | 3553 | 410.41 |
| Frank H. P. Fitzek | 10 | 706 | 123.89 |
| Hans D. Schotten | 11 | 231 | 86.45 |
| Slawomir Stanczak | 12 | 521 | 89.71 |