Threshold-Triggered Selective Phase-Forward of Differential PSK in Cooperative Communication
Bibliographic record
Abstract
We study in this paper the performance of a one-way cooperative transmission system using differential PSK (DPSK) modulation with differential detection. As opposed to previous works which consider either a decode-and-forward (DF) or an amplify-and-forward (AF) relay, we adopt in this paper a phase-forward (PF) relay, whereby each forwarded symbol has constant modulus and a phase equals the phase of the corresponding relay's received symbol. The rationale for adopting this relaying strategy is to avoid potential non-linear amplifier distortion in an amplify-and-forward relay, as well as the implicit information loss/quantization in a DF relay. Through analysis and simulation, we found that this PF-DPSK cooperative transmission scheme has a lower bit-error rate (BER) than that of its DF counterpart. Furthermore, by adopting a threshold-based selective forwarding approach, it can attain a BER similar to that of AF. Finally, we anticipate that PF is most useful in two or multi-way relaying, in which any non-linear amplifier distortion on an AF signal will manifest into significant inter-modulation.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".