Compress-forward without Wyner-Ziv binning for the one-way and two-way relay channels
Bibliographic record
Abstract
We consider the role of Wyner-Ziv binning in compress-forward for relay channels. In the one-way relay channel, we analyze a compress-forward scheme without Wyner- Ziv binning but with joint decoding of both the message and compression index. It achieves the same rate as the original compress-forward scheme with binning and successive decoding. Therefore, binning helps reduce decoding complexity by allowing successive decoding, but has no impact on achievable rate for the one-way relay channel. On the other hand, no binning simplifies relay operation. By extending compress-forward without binning to the two-way relay channel, we can achieve a larger rate region than the original compress-forward scheme when the channel is asymmetric for the two users. Binning and successive decoding limits the compression rate to match the weaker of the channels from relay to two users, whereas without binning, this restriction no longer applies. Compared with noisy network coding, compress-forward without binning achieves the same rate region in certain Gaussian channel configurations, and it has much less delay. This work is a step toward understanding the role of Wyner-Ziv binning in compress-forward relaying.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".