A generalized simplified ML decoder of orthogonal space-time block code for wireless communications over time-selective fading channels
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Bibliographic record
Abstract
We propose a novel generalized simplified maximum-likelihood (ML) decoder of orthogonal space-time block code (OSTBC) for wireless communications over time-selective fading channels. The proposed decoder computes the decision statistics based on the channel state information (CSI) and completely removes the inter-transmit-antenna interference (ITAI) and provides diversity advantage when the channel varies from one signaling interval to another. It is shown that when the channel is quasi-static, the proposed decoder becomes the optimum ML decoder for OSTBC. We derive a tight theoretical upper bound for bit error probability of the proposed decoder. We show theoretically that the proposed decoder does not exhibit error floors at high signal-to-noise ratios (SNR). Simulation results for various channel-fading rates are presented to verify our theoretical analysis and demonstrate robust performance of the proposed decoder.
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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 | 0.000 |
| 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