WLC16-3: Performance Analysis and Optimal Signal Designs for Minimum Decoding Complexity ABBA Codes
Bibliographic record
Abstract
ABBA codes, a class of quasi-orthogonal space-time block codes (STBC) proposed by Tirkkonen et al., have been studied extensively for various applications. Yuen et al. have recently shown that a refined version of ABBA codes admit pair-wise real-symbol decoding, i.e. with minimum decoding complexity (MDC) achievable by non-orthogonal STBC. In this paper, we derive the exact symbol pair-wise error probability and the union bound on the symbol error rate (SER). The union bound is only 0.1 dB from the simulated SER at medium or high SNR < 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-2</sup> . Thus, by minimizing the SER union bound, we can find the optimal signal designs for any constellation with an arbitrary geometrical shape. Furthermore, we propose a new method combining signal rotation and power allocation for inphase-quadrature power-unbalanced constellations such as rectangular QAM. Our new optimal signal designs perform better than the existing ones and offer lower encoding/decoding complexities.
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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".