A Survey on Multiuser SWIPT Communications for 5G+
Bibliographic record
Abstract
Increasing number of devices connected to the networks, applications and demands of new generation wireless communications cause very high energy consumption resulting in large amount of carbon emission. Thus, energy harvesting solutions together with accomplishing information transmission are required for energy efficient communications of new wireless communications generations such as 5G and 6G (i.e., 5G+). As such, due to the promise of energy efficient green communications, simultaneous wireless information and power transfer (SWIPT) techniques are expected to be indispensable component of 5G+. In this survey, the literature of multiuser SWIPT communications is reviewed for 5G+. Different multiuser SWIPT scenarios including multi-antenna communications, cooperative communications, network coding, communications security, and unmanned aerial vehicle (UAV)-enabled communication systems based on multiuser diversity and multiple access methods are thoroughly reviewed. The experimental studies are also discussed.
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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 | 0.001 | 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".