Soft Input Error Resilient Multiple Description Coding for Rayleigh Fading Channels
Why this work is in the frame
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Bibliographic record
Abstract
Error resilient multiple description coding (ERMDC) consists of a robust encoder and an enhanced decoder. It was developed to achieve higher error tolerance than the classical multiple description coding (MDC) for error-prone channels when bit errors of one description exceeded the error correction capability of the applied forward error correction (FEC) code. In this paper, ERMDC is extended to Rayleigh fading channels with additive white Gaussian noise (AWGN) by utilizing soft channel outputs. By using soft channel outputs as receiver inputs, the accuracy of estimates of detectable transmission errors is improved so that the reconstruction distortion is reduced further. Experimental results show that soft input ERMDC outperforms significantly the existing works without extra redundancy.
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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 | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 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