Linear Receive Beamforming for Continuous-Aperture Array (CAPA) Systems
Bibliographic record
Abstract
The performance of linear receive beamforming in continuous-aperture array (CAPA)-based uplink communications is investigated. Three continuous beamforming strategies are proposed based on the principles of maximum-ratio combining (MRC), zero-forcing (ZF), and maximum signal-to-interference-plus-noise ratio (SINR) (i.e., optimal beamforming). For MRC beamforming, closed-form expressions for both the beamformer and the achievable sum-rate are derived. For ZF beamforming, a closed-form solution is developed using channel correlation to effectively eliminate inter-user interference. For optimal beamforming, a closed-form beamformer is obtained by solving an operator-based Rayleigh quotient maximization problem, and the associated achievable sum-rate is characterized. Numerical results confirm that CAPAs outperform traditional spatially-discrete arrays (SPDAs), achieving superior sum-rate performance under all three beamforming schemes.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".