Distributed Alamouti Relay Beamforming Scheme in Multiuser Relay Networks
Why this work is in the frame
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Bibliographic record
Abstract
We design distributed relay beamforming in a multiuser peer-to-peer relay network. By exploring Alamouti code at both sources and relays, we propose a rank-two Alamouti-based distributed relay beamforming scheme to minimize per relay power, while meeting the signal-to-interference-and-noise ratio targets. For the nonconvex optimization problem, we propose a rank-constrained separable semidefinite relaxation approach to find an approximate solution, and provide conditions for which it produces an optimal solution and a bound on the gap to the optimal performance. Compared with the traditional rank-one distributed relay beamforming scheme, our proposed Alamouti-based rank-two distributed relay beamforming offers a significantly higher likelihood to produce an optimal solution and a better capability to maintain small performance degradation as the network size increases. As a result, it provides substantially improved relay power efficiency.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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