A rate-control scheme for video transport over wireless channels
Bibliographic record
Abstract
We investigate the scenario of using the automatic repeat request (ARQ) retransmission scheme for two-way video communications over wireless Rayleigh fading channels. Video quality is the major concern of these applications. We show that, during the retransmissions of error packets, due to the reduced channel throughput, the video encoder buffer may fill-up quickly and cause the TMN8 rate-control algorithm to significantly reduce the bits allocated to each video frame. This results in PSNR degradation and many skipped frames. To minimize the number of frames skipped, we propose improved rate-control schemes that take into consideration the effects of the video buffer fill-up, an a priori channel model, and the channel feedback information. We also show that a discrete cosine transform (DCT) coefficient soft-thresholding scheme can be applied to further improve video quality. As a result, our proposed rate-control schemes encode the video sequences with less frame skipping and with higher PSNR compared to TMN8.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".