A Terminal-Assisted Bayesian Broadcasting Algorithm for S-ALOHA Systems with Finite Population of Multi-Buffered Terminals
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Bibliographic record
Abstract
This letter proposes a backoff algorithm for slotted ALOHA (S-ALOHA) systems with multi-buffered terminals. According to the proposed algorithm, a base station (BS) broadcasts a retransmission probability based on estimated backlog size, while the terminals help the BS to estimate the backlog size by sending a one-bit backlog indication piggybacked on the information packet upon a successful random access. We present the performance of the proposed algorithm in terms of mean and variance of system response time, and compare them against existing algorithms and the optimal one. Results show that the proposed algorithm can improve the performance significantly especially for high packet arrival rates, small population size and asymmetric traffic cases.
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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 | 0.001 |
| Open science | 0.002 | 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