Uncoordinated Distributed Space-Time Trellis Coding
Bibliographic record
Abstract
In this paper, we introduce a new class of distributed space-time trellis codes (DSTTCs) for wireless networks with a large set of decode-and-forward relay nodes N. It is assumed that at any given time only a small, a priori unknown subset of nodes S - N is active. We consider the general case where each relay node is equipped with NT antennas and the destination node has NR antennas. In the novel distributed space-time trellis coding scheme each relay node is assigned a unique signature matrix but all active nodes use the same trellis for encoding. Efficient methods for the optimization of the set of signature matrices are provided and it is shown that existing full-rank STTCs designed for Nc - 2 co-located antennas are a favorable choice for the trelis encoding. If properly designed, the proposed DSTTCs achieve a diversity order of d = min{NcNR, NTNSNR} if NS nodes are active. Simulation results show the superior performance of the novel DSTTCs compared to distributed space-time filtering and distributed space-time block coding.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.005 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".