Joint rate and cluster optimization in cooperative MIMO sensor networks
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We design transmission schemes in cooperative MIMO sensor networks that optimize the choice of rate and cluster for minimizing the energy consumption subject to a given average probability of error. In general it was observed that, the number of clusters to optimize the energy consumption is a non-increasing function of long haul distance. By virtue of this, we conclude that as the long haul distance increases the cooperation among the nodes increases. Also, for large long haul distances the optimal number of clusters is shown to converge to a constant. Next, we propose a provably convergent block coordinate descent algorithm to determine the optimal joint rate and number of clusters. Through our numerical results it was observed that a cluster optimized cooperative MIMO transmission scheme can be more energy efficient than a rate only optimized scheme. Also a joint rate and cluster optimized transmission scheme can yield large scale energy savings for short and medium range applications compared to the rate only or cluster only optimized transmission schemes.
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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 it