Constrained detection for multiple-input multiple-output channels
Why this work is in the frame
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Bibliographic record
Abstract
We develop a family of constrained detectors for multiple-input multiple-output (MIMO) channels by relaxing the maximum likelihood (ML) detection problem. Real constrained linear detectors and decision feedback detectors are proposed for real constellations by forcing the relaxed solution to be real. Generalized minimum mean-square error and constrained least squares detectors are generalized as MIMO detectors for both constant and non-constant modulus constellations. Using our constrained linear detectors, we propose a new ordering scheme to achieve a tradeoff between interference suppression and noise enhancement. Moreover, we introduce a combined constrained linear and decision feedback detector to mitigate the error propagation in decision feedback. Simulation results show that the combined detectors achieve significant performance gain over V-BLAST 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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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