Bibliographic record
Abstract
Space-time (ST) coding is an efficient technique for combatting short-term fading in telecommunication systems with multiple transmit antennas. This paper presents a multi-dimensional framework for such a system that contrasts two approaches for assigning signal dimensions to antennas. With aggregate transmit antennas (ATA), a dimension is employed by all the antennas while in orthogonal transmit antennas (OTA), each dimension is employed by a single transmit antenna. We provide a diversity order analysis for repetition codes and Tarokh-Seshadri-Calderbank (see IEEE Transactions on Information Theory, vol.44, p.744-64, 1998) codes within our framework over a spatially uncorrelated, block-fading Rayleigh channel. Simulation results for repetition, TSC, and classical convolutional codes using both OTA and ATA transmission are presented. With ATA, classical convolutional codes perform comparably to the known TSC codes, while with OTA diversity gain is easier to obtain than with ATA. All the codes that were considered in this work with OTA show performance gains with respect to ATA.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".