Optimization of Hierarchical Modulation for Decode-and-Forward Wireless Relay Networks
Bibliographic record
Abstract
This paper presents two designs of optimal nonuniformed constellations for decode-and-forward wireless relay networks with an orthogonal space-time block code (STBC). The first design is concerned with the unequal error protection issue, in which two data streams to be transmitted from a source to a destination are protected at two different levels. The design is to minimize the bit error rate (BER) of one stream while maintaining the BER of the other stream to be no larger than a given threshold. Based on a simple approximation of the average BER, a design parameter is obtained in closed form. The second design focuses on minimizing the average BER of the combined data stream at the destination. Developed are two near-optimal designs for 4/16-quadrature amplitude modulation (QAM) and 4/64-QAM hierarchical modulation (HM) schemes. The designs are also extended to two-way relay networks where both the source and the destination have data to transmit to each other. Simulation results confirm the superiority of the proposed designs and the advantages of relay-assisted transmission employing HM over conventional point-to-point transmission. A comparison with the existing relay-assisted transmission model is also discussed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".