Short-Term Multivariate KPI Forecasting in Rural Fixed Wireless LTE Networks
Why this work is in the frame
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Bibliographic record
Abstract
Time series forecasting has gained significant traction in LTE networks as a way to enable dynamic resource allocation, upgrade planning, and anomaly detection. This letter investigates short-term key performance indicator (KPI) forecasting for rural fixed wireless LTE networks. We show that rural fixed wireless LTE KPIs have shorter temporal dependencies compared to urban mobile networks. Second, we identify that the inclusion of environmental exogenous features yields minimal accuracy improvements. Finally, we find that sequence-to-sequence-based (Seq2Seq) models outperform simpler recurrent neural network (RNN) models, such as long short-term memory (LSTM) and gated recurrent unit (GRU), and random forest (RF).
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it