Coding with dynamic rate control for low-delay image transmission over CDMA fading channels
Bibliographic record
Abstract
In the context of low-delay reliable image transmission over CDMA slowly Rayleigh fading channels, this paper addresses the proposal of a coding control technique that dynamically adapts the source coder rate to the channel condition, in order to transmit coded image data with low delay. In previous work, we proposed tools for error-resilient coding in order to improve the quality of transmitted images over the aforementioned channel. However, in case of degrading channel conditions, an increase in the transmission delay may result due to the use of an equal ARQ error control for all coded image data. Therefore, we propose to decrease the volume of coded data when the channel is in poor condition to decrease the amount of data to be transmitted with ARQ, and hence reduce the image transmission delay. The approach proposed to dynamically control the coder rate to the channel condition is based on an estimate of the channel status. The scheme proposed is shown to offer acceptable delay and high resistance to transmission errors.
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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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".