Comparison of ARQ protocols for asynchronous data transmission over Rayleigh fading channels
Bibliographic record
Abstract
the authors examine error control techniques for the transmission of asynchronous data over Rayleigh fading channels. Type-I hybrid ARQ schemes are considered with rate 1/2 convolutional coding for FEC. The protocols are evaluated over a full rate North American Digital Cellular channel with the goal of achieving 4.8 kbit/s asynchronous data transmission. Throughput and round trip acknowledgment delay (RTAD) results are presented for various vehicle speeds. The Go-Back-N ARQ (GEN-ARQ) protocol, and four different versions of the Selective-Repeat ARQ (SR-ARQ) protocol are compared. The relative performance of the different ARQ protocols is discussed. A version of the selective repeat protocol, which combines the error recovery mechanisms of GBN-ARQ. The pure selective repeat protocol and other enhancements, provides the best compromise in terms of throughput and delay performance over the range of different speeds and SNR conditions.>
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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 | 0.005 | 0.012 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".