Coherent space-time codes for noncoherent channels
Bibliographic record
Abstract
A new algebraic formulation for the diversity advantage design criterion for arbitrary space-time signals in noncoherent block fading channels is developed. It is shown that the new criterion encompasses, as a special case, the well-known diversity advantage criterion for unitary space-time signaling. Using the proposed criterion, the optimal diversity-vs-rate tradeoff is derived for training based noncoherent signaling schemes. Our results are then specialized to the class of affine space-time signals which allow for an efficient polynomial complexity decoder. Within this class, new space-time constellations based on the threaded algebraic space-time (TAST) framework are proposed. These codes achieve the optimal diversity-vs-rate tradeoff and outperform previously proposed codes in the considered scenarios as demonstrated by numerical results. Using these analytical and numerical results, we argue that non-unitary space-time codes offer certain advantages in block fading channels and the appropriate use of coherent space-time codes is shown to offer a very efficient solution to the noncoherent space-time communication paradigm.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".