Performance of combined channel coding and space-time block coding with antenna selection
Bibliographic record
Abstract
We analyzed the performance of the serial concatenation of convolutional coding with space-time block coding. We obtained an error bound for the space-time coded system with ideal channel interleaving. Our results indicated that these error bounds are in a good agreement with the exact BER performance especially at low BER levels where error bounds become more significant. We have also shown that the use of antenna selection at the receiver side only effects the SNR coding gain, but not the overall diversity order. This phenomena was evident for both the fast and block flat fading channel models. Moreover, we have shown that the receiver performance is affected significantly by channel interleaving. In that, a comparison between the quasi-static and fast fading channels was conducted where it was shown that the time diversity order dominates the overall system diversity. Furthermore, we have noted that the use of antenna selection results in almost the same SNR reduction regardless of the channel model used.
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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".