On Optimality of Monotone Channel-Aware Transmission Policies: A Constrained Markov Decision Process Approach
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Bibliographic record
Abstract
A constrained Markov decision process (MDP) approach is deployed to prove the monotone structure of optimal channel-aware transmission policies for packet transmission over a correlated fading wireless channel subject to an average delay constraint. A transmission policy is a function mapping channel state information (CSI), buffer states and numbers of arriving packets to transmit probabilities. The objective is to minimize the average transmission energy cost subject to an average delay constraint. We use the Lagrange multiplier method to convert the constrained MDP to an unconstrained MDP and prove that the unconstrained optimal policy is threshold in the buffer state. It then follows that the constrained optimal transmission policy is a randomized mixture of two pure transmission policies that are threshold in the buffer occupancy.
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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