Performance Analysis of Cognitive Wireless Powered Communication Networks Under Unsaturated Traffic Condition
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
By improving the efficiency of wireless power transfer (WPT), wireless powered communication networks (WPCNs) are receiving increasing attention. WPCN provides untethered mobility and prolongs the network lifetime by eliminating the need for repetitive charging and replacement of the battery. In this paper, we consider a cognitive WPCN in which wireless powered secondary users (SUs) opportunistically exploit the spectrum licensed to the primary users (PUs). Each SU is associated with a power beacon (PB) node which is responsible for charging the corresponding SU and receiving its data over different frequency bands. SUs have unsaturated data traffic and can transmit if they are out of any guard zone which is defined around active PUs to prevent strong interference. Using tools from stochastic geometry and queueing theory, we characterize the effects of the randomness in data and energy availability of SUs on the interference among PUs and SUs. Then, we derive the service time distribution, mean waiting time, and queue stability criterion for a typical SU, as well as the outage probability of a typical PU. Finally, through extensive simulations, the analytical results are evaluated and the effects of different parameters on the network performance are studied.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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 it