Time Series Forecasting
Collection
This collection offers papers and resources on time-series forecasting, with a focus on its applications in telecom networks
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2 items
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Updated
Datasets:
📶 Beam-Level (5G) Time-Series Dataset
This dataset introduces a novel multivariate time series specifically curated to support research in enabling accurate prediction of KPIs across communication networks, as illustrated below:
Precise forecasting of network traffic is critical for optimizing network management and enhancing resource allocation efficiency. This task is of both practical and theoretical importance to researchers in networking and machine learning, offering a strong benchmark for state-of-the-art (SOTA) time series models.
📂 Dataset Overview
The dataset comprises:
- 2,880 Beams across 30 Base Stations (3 Cells per Station, 32 Beams per Cell).
- Duration: 5 weeks + 2 target weeks, totaling up to 840 training hours and 1176 total hours per beam.
📁 Available CSV Files
🏋️♂️ Training Set (Weeks 0–5)
| File Name | Metric |
|---|---|
DLThpVol_train_0w-5w.csv |
Downlink throughput volume |
DLThpTime_train_0w-5w.csv |
Throughput transmission time |
DLPRB_train_0w-5w.csv |
PRB (Physical Resource Block) usage |
MR_number_train_0w-5w.csv |
User count (Measurement Reports) |
🎯 Forecast Targets
📆 6th Week (Week 5–6)
| File Name | Metric |
|---|---|
DLThpVol_test_5w-6w.csv |
Downlink throughput volume |
DLThpTime_test_5w-6w.csv |
Throughput transmission time |
DLPRB_test_5w-6w.csv |
PRB usage |
MR_number_test_5w-6w.csv |
User count |
📆 11th Week (Week 10–11)
| File Name | Metric |
|---|---|
DLThpVol_test_10w-11w.csv |
Downlink throughput volume |
DLThpTime_test_10w-11w.csv |
Throughput transmission time |
DLPRB_test_10w-11w.csv |
PRB usage |
MR_number_test_10w-11w.csv |
User count |
🧪 Dataset Splits
The dataset is split into a Training Set (first 5 weeks) and Forecast Targets for Week 6 (immediate future) and Week 11 (long-term future).
📄 Data Format
Each CSV file contains a Time column and multiple beam columns (e.g., 0_0_0 to 29_2_31). The Time column ranges from 0–839 for training (weeks 1–6), 0–167 for week 6, and 168–335 for week 11. Each beam column uniquely identifies one of the 2,880 beams across 30 base stations.
📚 Citation
If you use this dataset in your research, please cite:
L. Fechete et al., Goal-Oriented Time-Series Forecasting: Foundation Framework Design, arXiv:2504.17493 (2025)
🔗 Code Repository
The official codebase for working with this dataset is available here: 👉 https://github.com/netop-team/gotsf
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