Optimized Nonuniform Constellation Rearrangement for Cooperative Relaying
Bibliographic record
Abstract
The performance of cooperative relaying networks can be significantly enhanced by using constellation rearrangement (CoRe). In CoRe, the base-station and the relay-station use different constellations, each having the same number of signal points, to communicate with the user terminal. A number of CoRe schemes have been proposed in the literature based on uniform quadrature-amplitude modulation (QAM) constellations. However, it is still unclear whether nonuniform QAM constellations can further enhance the performance of CoRe. Toward this end, we investigate the problem of designing the optimum nonuniform QAM constellations for CoRe. Our motivation is that nonuniform constellations have the potential to outperform their uniform counterparts because the set of nonuniform constellations is a superset of uniform constellations. Nonuniform QAM constellations can be categorized as either decomposable or nondecomposable . Unlike nondecomposable QAM constellations, decomposable QAM constellations are generated from the Cartesian product of two pulse-amplitude modulation (PAM) constellations. We formulate an optimization problem to find the nonuniform constellations that have the minimum union bound on the uncoded symbol error rate (SER). Using convex analysis, we devise a search method to find globally optimum nonuniform decomposable constellations. We also devise a simple heuristic to find good locally optimum nonuniform nondecomposable constellations, which perform better than their decomposable counterparts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".