Turbo decoding for precoded systems over multipath fading channels
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Bibliographic record
Abstract
A combined precoding and turbo decoding strategy for multi-path frequency-selective fading channels is presented. The precoder and multi-path fading channel are jointly modeled as a finite-state probabilistic channel to provide the multistage turbo decoder with its statistics information. Both a priori and a posteriori probabilities are used in the metric computation to improve the system performance. Structures of the combined turbo-encoder, interleaver, and precoder in the transmitter and two-stage turbo decoder in the receiver are described. Performance of the proposed scheme in fixed, Rician and Rayleigh multi-path fading channels are evaluated by simulation. The results indicate that the combined precoding and two-stage turbo decoding strategy provides a considerable performance improvement while maintaining the same inner structure of a conventional turbo decoder.
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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 | 0.000 | 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 | 0.001 | 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