An ICI-Aware Scheduler for NB-IoT Devices in Co-existence with 5G NR
Bibliographic record
Abstract
5G New Radio (NR) and Narrowband Internet-of-Things (NB-IoT) co-existence is a promising technique to improve scalability and flexibility of future cellular networks. In this paper, we study the performance of an ICI-limited 5G NR based multi-cell network with a number of NB-IoT devices sharing a dedicated in-band resource block (RB). We propose a unified scheduler for maximizing instantaneous throughput and fairness over each RB. Numerical simulations with realistic inter-cell-interference (ICI) parameters have been used to evaluate the performance of the proposed RB allocation scheme for both NB-IoT devices and 5G NR UEs in an urban scenario. Our simulation results provide useful insights for designing a unified ICI-aware scheduler for 5G NR systems that can work in co-existence with various type of IoT devices.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".