Half-duplex relaying over slow fading multiple access channel
Bibliographic record
Abstract
This paper investigates the half-duplex (HD) relaying in the slow fading Multiple Access Channel (MAC) based on the generalized quantize-and-forward (GQF) scheme. Relay listens to the channel in the first slot of the transmission block and cooperatively transmits to the destination in the second slot. The achievable rate regions of the discrete memoryless HD-MARC and the corresponding additive white Gaussian noise (AWGN) channel have been established first. Based on the achievable rates, the outage probability and expected sum rate are characterized as the performance measure of the slow fading channel. It is shown that when the relay has no access to the channel state information (CSI) of the relay-destination link, the GQF scheme outperforms other relaying schemes, e.g., compress-and-forward (CF), decode-and-forward (DF) and amplify-and-forward (AF). In addition, for a MAC with heterogeneous user channels and quality-of-service (QoS) requirements, the individual outage probability and expected sum rate of the GQF scheme are also obtained and shown outperform the CF scheme.
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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 | 0.001 |
| 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 | 0.001 | 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 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".