Ergodic Capacity Analysis of Full Duplex Relaying in the Presence of Co-Channel Interference in V2V Communications
Bibliographic record
Abstract
fading channels. In this context, the impacts of self-interference (SI) at the relay and co-channel interference (CCI) at the destination are taken into account in this analysis. Precisely, based on the analysis of the moment generating function (MGF) of the signal-to-interference-plus-noise ratio (SINR), new exact and lower bound expressions for the ergodic capacity are derived. The ergodic capacity upper bound is also derived based on the asymptotic outage probability of the approximated SINR. Monte-Carlo simulation results are presented to corroborate the derived analytical results. Our results show the significant impact of the considered interferences on the system performance. It is shown that the ergodic capacity is degraded when the average SI at the relay and/or the average CCI at the destination is increased. This highlights the importance of taking these phenomena into account in the performance evaluation in order to assess the practical limit of full duplex relaying (FDR) cooperative wireless communications. Interestingly, it is also observed that FDR with SI and CCI still shows a higher ergodic capacity than the interference-free half duplex relaying, especially at medium to high signal-to-noise ratios (SNRs).
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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 | 0.007 |
| 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 | 0.001 | 0.001 |
| 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".