Multiuser Full-Duplex IoT Networks With Wireless-Powered Relaying: Performance Analysis and Energy Efficiency Optimization
Bibliographic record
Abstract
This paper considers an Internet-of-Things (IoT) network where a multi-antenna access point (AP) and several single-antenna IoT devices (IoDs), operating under the full-duplex (FD) mode, communicate with each other bidirectionally through the help of a wireless-powered FD relay. In particular, the power splitting (PS) protocol is adopted at the amplify-and-forward (AF) relay to implement a simultaneous wireless information and power transfer (SWIPT) receiver. For such a multiuser FD-IoT network assisted by a wireless-powered two-way relay, we derive exact overall outage probability (OOP) expressions and tight closed-form expressions for the ergodic sum rate (ESR) under generalized Nakagami-m fading channels. Furthermore, aiming to maximize the energy efficiency (EE), we obtain optimal power allocation (OPA) under the total power and rate threshold constraints. Finally, extensive numerical and simulation results are presented to corroborate our analytical findings.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".