MMC05-4: On the Optimality of Threshold Scheduling Policies for Video Transmission in Markovian Fading Wireless Channels with Channel-Aware ARQ
Bibliographic record
Abstract
We consider the problem of optimal transmission scheduling for real time multimedia (video) data transmission over wireless communication links. It is assumed that the wireless channel is Rayleigh fading and can be represented by a finite state Markov chain (FSMC) model, and that retransmissions are allowed via the use of an ARQ protocol. Due to a delay constraint, there is a limit on the number of time slots that may be used to transmit some (pre-designed) number of packets. The problem of optimal transmission scheduling is formulated as a finite horizon Markov decision process (MDP) with a cost function that takes into account the transmission cost and a penalty cost on the packet loss rate. Using the concept of supermodularity and convexity on the optimal cost and immediate cost functions, we prove that the optimal transmission scheduling policy is a threshold function of time and buffer size. These threshold policies are applicable for any delay-sensitive real time packet transmission system. Finally, the theoretical results are illustrated via numerical examples.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".