On the ergodic sum rate for multisource multidestination unmanned aerial vehicle relaying
Bibliographic record
Abstract
Abstract Unmanned aerial vehicle (UAV) relay system has received significant attention in future wireless communications. In this article, the ergodic sum rate of a multisource multidestination UAV relaying is investigated. Here, an UAV with multiple antennas is deployed as an aerial relay using threshold‐based decode‐and‐forward protocol to assist signal transmission from multiple sources to their intended destinations simultaneously. By considering the effect of path loss, we first obtain the output signal‐to‐interference‐plus‐noise ratio expression for the considered system. Then, we propose a statistical channel state information based beamforming (SCSI‐BF) scheme to maximize the system ergodic sum rate, where both of the uplink and downlink channels are subject to correlated Rayleigh fading. Furthermore, we derive the analytical expression for the ergodic sum rate of the considered system with the SCSI‐BF scheme. Finally, numerical results are given to demonstrate the superiority of the SCSI‐BF scheme and the validity of the theoretical analysis, and show the impact of various parameters on the system performance.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".