On the performance of trellis-coded modulation in digital microwave radio
Bibliographic record
Abstract
Trellis-coded modulation (TCM) techniques are considered for use in a digital microwave radio (DMR) system employing high-level M-QAM modulation. Emphasis is placed on whether the coding gain offered at high signal-to-noise ratio is also in effect during deep selective fades. A specific Ungerboeck code, used in a 512-cross modulation scheme was found to have a lower probability of outage (for a bit-error-rate (BER) threshold of 10/sup -3/), than an uncoded 256-QAM system having the same symbol rate. The same linear adaptive finite-tap transversal equalizer was used in both the uncoded and the coded systems. Further work was done to see what effect various code parameters had on the fade performance. The result was that the TCM system always outperformed the uncoded system (up to a BER of 10/sup -3/) under deep selective fades.>
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".