On the design of Grassmannian constellations for non-coherent MIMO communication systems
Bibliographic record
Abstract
We consider the design of the Grassmannian constellations that are required for rate-efficient non-coherent wireless MIMO communication. We begin by providing insight into the way in which these constellations are structured, and we then provide two new techniques for designing them. The first technique enables joint design of all the constellation points by exploiting a new method (proposed herein) for simultaneous optimization of multiple points on the Grassmann manifold. This in contrast to most existing techniques in which the points are designed sequentially. The second technique is a more efficient method for designing large constellations. By expressing large constellations as the disjoint union of rotated versions of a 'proto-constellation', one can partition the design problem into the design of a (small) proto-constellation and that of the rotation matrices. It will be shown that, in addition to providing storage and regeneration convenience, the rotation-based design retains two desirable features of the optimal design. Finally, we will provide numerical simulations that illustrate the performance of the constellations designed with the proposed techniques.
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 | 0.000 |
| 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".