Gaussian multiple-access relay channels with non-causal side information at the transmitters
Bibliographic record
Abstract
The multiple-access relay channel (MARC) and its Gaussian version are important models in cellular, ad hoc communication systems, and sensor networks and also, this channel is a comprehensive model which consist of two important channels: Relay Channel (RC) and Multiple Access Channel (MAC). In this paper, we study and analyse the two-user state-dependent discrete and memoryless MARC in which the independent states of channel are known non-causally only at the encoders. An achievable rate region by using binning and decode-and-forward (DF) schemes and an outer bound for this model are obtained. We also by using our results obtain an inner bound for two-user Gaussian MARC with identical non-causal side information. Our model includes discrete and continuous (Gaussian) multiple access channel rate region and relay channel rate with non-causal side information. Finally, we evaluate our bounds for Gaussian MARC numerically and illustrate the effect of interference power on bounds.
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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 | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 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 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".