WLC21-1: Improved High-rate Space-Time-Frequency Block Codes
Bibliographic record
Abstract
High-rate space-time-frequency block codes (STFBC) are promising for achieving high bandwidth efficiency, low overhead and latency. Recently, a class of low-complexity STFBC methods based on two stages of complex diversity coding (CDC) have been proposed, known as double linear dispersion STFC(DLD-STFC). This paper investigates two issues related to the performance improvement of high-rate STFCs. First, it is shown that the two CDC stages of DLD-STFC can be interchanged. Two new diversity concepts for analysis of 3-dimensional DLD-STFC are introduced: per dimension diversity order and per dimension symbol-wise diversity order. A sufficient condition for DLD-STFC to achieve full symbol-wise diversity order is provided despite the existence of two CDC stages. Second, the gain obtainable in combining CDC with forward error correction (FEC) for STFC designs is quantified. Through simulations, it is shown that STFC based on the proper combination of CDC and FEC may outperform a variety of other STFC combinations, especially in spatially correlated channels. Further, the choice of the mapping from FEC to DLD-STFC may significantly impact system performance.
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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".