Source–Channel Communication Over Phase-Incoherent Multiuser Channels
Bibliographic record
Abstract
We study the transmission of two correlated and memoryless sources (U1, U2) over several multiuser phase asynchronous channels. Namely, we consider a multiple access relay channel (MARC) with causal, and a MARC with non-causal unidirectional cooperation between encoders, referred to as phase-incoherent causal (respectively, non-causal) cognitive MARCs. We also consider phase-incoherent interference channel models with and without relay, in the same context. In all cases, the input signals are assumed to undergo non-ergodic phase shifts, which are unknown to the transmitters and known to the receivers as a realistic assumption. Both necessary and sufficient conditions in order to reliably send the correlated sources to the destinations are derived. In particular, for all of the channel models, by using a key lemma, we first derive an outer bound for reliable communication. Then, using separate source and channel coding and under specific gain conditions, we establish the same region as the inner bound. We thus conclude that without the knowledge of the phase shifts at transmitters, and under specific gain conditions, separation is optimal.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".