Power efficient and secure multiuser communication systems with wireless information and power transfer
Bibliographic record
Abstract
In this paper, we study resource allocation algorithm design for power efficient secure communication with simultaneous wireless information and power transfer (WIPT) in multiuser communication systems. In particular, we focus on power splitting receivers which are able to harvest energy and decode information from the received signals. The considered problem is modeled as an optimization problem which takes into account a minimum required signal-to-interference-plus-noise ratio (SINR) at multiple desired receivers, a maximum tolerable data rate at multiple multi-antenna potential eavesdroppers, and a minimum required power delivered to the receivers. The proposed problem formulation facilitates the dual use of artificial noise in providing efficient energy transfer and guaranteeing secure communication. We aim at minimizing the total transmit power by jointly optimizing transmit beamforming vectors, power splitting ratios at the desired receivers, and the covariance of the artificial noise. The resulting non-convex optimization problem is transformed into a semidefinite programming (SDP) and solved by SDP relaxation. We show that the adopted SDP relaxation is tight and achieves the global optimum of the original problem. Simulation results illustrate the significant power saving obtained by the proposed optimal algorithm compared to suboptimal baseline schemes.
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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 | 0.001 |
| 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".