A matching approach for power efficient relay selection in full duplex D2D networks
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
Full duplex relaying, which allows relays to transmit and receive signals simultaneously, can improve the spectrum efficiency and extend the range of device-to-device (D2D) communications. Due to the limited battery of mobile devices, it is essential to design a power-efficient relay selection scheme which can reduce the power consumption of devices and extend their lifetime. In this paper, we consider multiple D2D user pairs utilize full duplex relays to communicate using directional antennas. We formulate the power-efficient relay selection problem as a combinatorial optimization problem to minimize the power consumption of the mobile devices. Using a matching approach, we transform the problem into a one-to-one weighted bipartite matching problem. We then propose a power-efficient relay selection algorithm for relay-assisted D2D networks called PRS-D2D based on the Hungarian method to obtain the optimal solution in polynomial time. Simulation results show that our proposed algorithm improves the total power consumption of mobile devices by up to 32% comparing to an existing relay selection scheme in the literature.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it