On code design in joint MAC scheduling and wireless network coding
Bibliographic record
Abstract
In this paper, we investigate the problem of network coding and media scheduling in wireless multihop networks. Unique characteristics of the wireless media, such as omnidirectional transmissions and destructive interference, as well as the limitations of wireless nodes to either transmit or receive at any given time, imply new code design constraints for wireless networks. In this work, following the approach of Sagduyu et al., given a sufficient set of conflict-free link sets, we investigate necessary and sufficient conditions to design a capacity-achieving network coding solution for wireless networks. This approach uses a wired graph representation of the wireless network to design wireless network codes. Our study shows that the proposed approach works only if we preserve all of the code characteristics of the wired graph in the wireless one. We show the shortcoming of previous studies through a counterexample and explore this case further. The resulting insight is summarized in Theorem 1, which proves that unequal time shares allocated to conflict-free link sets will result in changing coding coefficients as the sets with larger time share are scheduled repeatedly.
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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 | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".