Joint User Scheduling for ODFMA-Based Multi-Cell Networks
Why this work is in the frame
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Bibliographic record
Abstract
This paper investigates the user scheduling (US) problem on the uplink (UL) and the downlink (DL) of an ODFMA-based multi-cell network. The US problem on UL is more challenging than the one on DL, because the UL inter-cell interference (ICI) strongly depends on the scheduling decisions of the neighboring cells, which can not be estimated in advance and the resulting US problem needs to be studied as a joint problem across multiple cells. This paper formulates this joint problem for both UL and DL, which is nonetheless a large scale mixed-integer linear problem (MINLP) that cannot be decoupled into multiple local US problems (one per cell) and it is also intractable in its exact form. Therefore, an upper bound US problem has been formulated using a novel continuous rate function that can be solved efficiently. Through extensive computations, we show that the upper bound problem provides a tight upper bound for the original joint US problem, hence, it can be used to obtain an off-line benchmark for US on both UL and DL of a multi-cell network.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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