Relay Selection and Max-Min Resource Allocation for Multi-Source OFDM-Based Mesh Networks
Bibliographic record
Abstract
We consider a multi-source mesh network of static access points wherein sources use decode-and-forward to cooperate with each other. All transmissions use orthogonal frequency division multiplexing (OFDM). Our objective is to maximize the minimum achievable rate across all flows. We find a tight upper bound on the performance of the subcarrier-based cooperation and show that selecting a single relay for each subcarrier is optimal for almost all subcarriers. The solution to the related optimization problem simultaneously solves the relay, power, and subcarrier assignment problems. Second, unlike previous works, we also consider relay selection for the entire OFDM block. This addresses the fact that, in addition to the synchronization problems caused, it is likely impractical for a relay to only decode a subset of subcarriers. We propose three selection-based cooperation schemes to relay the entire OFDM block with varying complexity. Simulation results show that under the COST-231 channel model, the performance of the simplest scheme almost exactly tracks that of an exhaustive search.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".