Hybrid-ARQ for layered space time MIMO systems with channel state information only at the receiver
Why this work is in the frame
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Bibliographic record
Abstract
The authors investigate hybrid automatic repeat request (H-ARQ) schemes for spatially multiplexed multiple-input multiple-output (MIMO) systems with channel state information available only at the receiver. In particular, the authors compare the multiple H-ARQ scheme and the single H-ARQ scheme with repetition. The authors first propose a system model for symbol detection for the multiple H-ARQ processes, and then discuss joint and separate detection algorithms for both multiple H-ARQ and single H-ARQ. Simulation results show that with linear detection the single H-ARQ outperforms multiple H-ARQ in the high signal-to-noise ratio region. With the vertical Bell Labs space-time (V-BLAST) architecture, multiple H-ARQ always outperforms single H-ARQ. Additionally, joint detection always outperforms separate detection.
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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 | 0.001 | 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 it