SPC03-1: On Decoding, Mutual Information, and Antenna Selection Diversity for Quasi-Orthogonal STBC with Minimum Decoding Complexity
Bibliographic record
Abstract
ABBA codes are an important class of quasi- orthogonal space-time block codes proposed by Tirkkonen et al.. Recently, they have become more attractive for practical applications because Yuen et al. have shown that ABBA codes allow pair-wise real-symbol decoding (or equivalently, single-complex symbol decoding) complexity; it is the minimum decoding complexity (MDC) achievable by any non-OSTBC. Additionally, MDC-ABBA codes can achieve full diversity while their code rate is higher than that of OSTBC. In this paper, we present anew,general,simple,andclosed-formmethod to decode MDC-ABBA codes. We explicitly derive the equivalent channel of MDC-ABBA codes and the maximum mutual information of MDC-ABBA. Furthermore, we prove that MDC-ABBA codes can achieve full diversity with transmit and/or receive antenna selection and full or limited feedback.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".