Effects of channel-estimation errors on receiver selection-combining schemes for Alamouti MIMO systems with BPSK
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Bibliographic record
Abstract
The bit-error rate (BER) of binary phase-shift keying in Rayleigh fading, using the Alamouti transmission scheme and receiver selection diversity in the presence of channel-estimation error, is studied. Closed-form expressions for the BER of log-likelihood ratio selection, signal-to-noise ratio (SNR) selection, switch-and-stay combining selection, and maximum ratio combining are derived in terms of the SNR and the cross-correlation coefficient of the channel gain and its corrupted estimate. Two new selection schemes, space-time sum-of-squares combining selection diversity and space-time sum-of-magnitudes selection diversity, are proposed and proven to provide almost the same performance as SNR selection, but with much simpler implementations. The effects of channel-estimation errors on each selection scheme are examined.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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