Non-coherent detection of alamouti-type space-time codes for PSK signal sets
Bibliographic record
Abstract
We consider the issue of non-coherent detection of Alamouti-type space-time (ST) modulations, employing phase- shift keying constellations and L receive antennas, in static Rayleigh fading channels. We observe that the two dominant eigenvectors of the received signal's correlation matrix are linear combinations of the two transmitted signal patterns. Consequently, we propose a receiver that recovers the transmitted patterns through linear combinations of these eigenvectors. Through the use of two scalar multiple-symbol differential detectors (MSDD), our receiver is able to perform low complexity sequence detection of the data contained in the two reconstructed patterns. The overall complexity of our receiver is 3 N , where N is the size of the MSDDs. This corresponds to a dramatic reduction from the exponential complexity of the optimal sequence detector for ST modulations. Our results show that for QPSK, N=64 and 3 receive antennas, the proposed receiver's performance is within 0.2-dB of the ideal coherent lower bound. Furthermore, with the proposed receiver processing methodology, there is no need for ST differential encoding; scalar differential encoding is sufficient. Keywords-Alamouti modulation, non-coherent detection, scalar- MSDD, eigen-decomposition.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".