Underlaid Full-Duplex D2D Cellular Networks: Modeling and Analysis
Bibliographic record
Abstract
In this paper, we provide an analytical performance characterization of underlaid device-to-device (D2D) cellular networks where D2D users operate in full-duplex (FD) mode under the presence of residual self-interference. In considered networks, the base-stations (BSs) are distributed according to a hexagonal grid, while the locations of cellular and D2D users follow Poisson point processes (PPPs). Based on stochastic-geometry approach, we develop the approximations of key performance metrics including coverage probabilities and ergodic sum-rates of both cellular and D2D links in order to investigate the benefits of integrating underlaid D2D communications in cellular networks in terms of spectral efficiency. The achieved approximations also allow to characterize the sum-rate behaviors under the effects of various system parameters. We show that underlaid D2D communications in cellular network can offer a significant spectral efficiency gain as compared to pure cellular transmission. With a sufficiently low self-interference cancellation level, FD D2D can offer substantial spectral efficiency improvement over the HD counterpart.
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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 | 0.001 |
| 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 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".