Distortion Exponents for Multi-Relay Cooperative Networks with Limited Feedback
Bibliographic record
Abstract
In this paper, we study the transmission of a Gaussian signal in a multi-relay cooperative system, where each relay is half-duplex and employs the amplify-and-forward (AF) relaying protocol. We focus on the analysis of the distortion exponent that characterizes the high signal-to-noise ratio (SNR) behavior of the end-to-end distortion of the received signal. Specifically, we investigate the feedback scheme where the limited channel state feedback is combined with separate source and channel coding to help the transmission. The feedback scheme is followed by three AF-based multi-relay cooperation protocols, respectively, namely the orthogonal AF protocol, the nonorthogonal AF protocol, and the slotted AF protocol. We derive the optimal distortion exponents of all three cases, and illustrate the effect of the feedback resolution, bandwidth ratio, and number of relays on the optimal distortion exponent. It is shown that the feedback scheme outperforms the best known non-feedback strategies for multi-relay cooperative systems with only a few bits of feedback information.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".