On the Properties of a Robust Timing Error Detector for Alamouti Space-Time Coding in Rayleigh Fading MIMO Channels with Randomly Distributed Timing Drift
Bibliographic record
Abstract
Abstract — We analyze the properties of a robust timing error detector for nT = 2 orthogonal space-time block coded M-PSK systems with an arbitrary number of receive antennas. The algorithm uses maximum-likelihood detection variables to estimate the timing error by examining the difference in threshold crossings. The S-curve of the detector is shown to be independent of the channel state, thus making it very robust in poor channel conditions. Furthermore, we derive a closed form expression for the variance of the estimator, and show that the estimation SNR peaks in the timing error region the receiver usually operates in. We evaluate the tracking performance in 1-, 2- and 4-receive antenna systems with randomly distributed timing drift. Complete channel state estimation is assumed throughout the paper. I.
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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 | 0.000 | 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 | 0.000 | 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".