Trellis coding of pi /4-QPSK signals for AWGN and fading channels
Bibliographic record
Abstract
A methodology for designing trellis coded modulation schemes that will conform to the pi /4-QPSK (quadrature phase-shift keying) modulation format is presented. The basic idea is to use multiple trellis codes with a signal set which is the Cartesian product of the even and odd subsets in the pi /4-QPSK signal constellation. Several good codes with a multiplicity of 2 are designed. Among them are an 8-state, rate 3/2 code with a throughput of 1.5 b/symbol and a 16-state, rate 2/2 code with a throughput of unity. The former can provide a second-order diversity effect in fading applications while the latter can provide a fifth-order diversity. In the AWGN (additive white Gaussian noise) channel, the rate 3/2 code is about .8 dB more energy efficient than the rate 2/2 code. Both codes compare favorably with conventional systems that use pi /4-QPSK in conjunction with convolutional coding. Based on the results obtained, it appears that trellis-coded modulation is a possible alternative to convolution code.>
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".