Turbo-coded transmission of smoothed H.263 video for the cdma2000 downlink
Bibliographic record
Abstract
H.263 video bitstreams can be characterized by high peak rates, frequent rate variations, and a high sensitivity to bit errors. Moreover, many interactive/streaming video applications require a tight bound on delay. The paper evaluates the performance of H.263 video transmission on the downlink of a cdma2000 system, and examines some of the tradeoffs needed in the design of such a system in order to meet the above requirements. In order to match the variable source rate to the bandwidth available to mobile cdma2000 video users, real-time smoothing of the video stream is performed prior to transmission. This introduces a delay at the video decoder which varies with the amount of buffering. To reduce the channel bit-error rate (BER), turbo coding is employed, which is also responsible for a delay at the receiver end. Hence, a tradeoff must be achieved between the amount of smoothing and error-correction, in order to respect the total end-to-end delay restrictions. Using entire system simulations, we assess the effects of the parameters of both the smoothing algorithm and the turbo coder on the received picture quality, for a given maximum delay: this work thus presents a joint optimization of real-time smoothing and turbo coding/decoding for H.263 video applications.
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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) | 0.000 | 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) | 0.001 | 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".