Sum-Power Minimization Under Rate Constraints in Full-Duplex MIMO Interference-Channels.
Bibliographic record
Abstract
We consider a full-duplex (FD) multiple-input multiple-output (MIMO) interference-channel, where multiple pairs of FD nodes coexist in the same network, and hence each node not only suffers from self-interference due to operating in FD mode, but also from co-channel-interference (CCI) from other pairs due to simultaneous transmission at each link. Transmission power expenditure is a significant source for power consumption in communication systems. One way to extend battery life is to utilize power-efficient resource allocation that minimizes the transmit power consumption. Therefore, in this paper we propose a penalty-based algorithm to address the Quality-of-Service (QoS) issue of this FD system where the total transmit power is minimized subject to minimum rate constraints at each node. The algorithm exploits both spatial and temporal freedoms of the source covariance matrices of MIMO links between the nodes to achieve a lower total system power. © 2017 VDE VERLAG GMBH.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".