RIS-based Passive Transmitter Reflection Optimization with Performance Complexity Trade-Offs
Bibliographic record
Abstract
This study considers a multiuser multiple-input multiple-output system realized via the reconfigurable intelligent surface-based passive transmitter setup, also known as modulating intelligent surface transmitter. The realistic assumption of discrete phase shifts of the reconfigurable intelligent surface’s elements is considered. Under this framework, the study formulates a symbol-level power minimization problem under the condition that the symbol-error probability is below a given requirement. Based on the proposed formulation a branch-and-bound algorithm is devised that improves on standard Full branch-and-bound approaches by accepting any solution that either attains the given target power budget of the system or is sufficiently close to the optimal such that it is considered unnecessary to continue the search process. Numerical results demonstrate the effectiveness of the proposed approach in minimizing the transmit power for different symbol-error probability requirements. Moreover, numerical results show that applying the proposed branch-and-bound approach instead of Full branch-and-bound techniques yields a negligible increase in transmit power for a significant reduction in computational complexity.
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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 | 0.000 |
| 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".