Adaptive physical-layer network coding in two-way relaying with OFDM
Bibliographic record
Abstract
Adaptive physical layer network coding (PNC) has been shown to be effective in two-way relay communications (TWRC). Given that the existing PNC methods were developed for frequency-flat fading channels, this paper studies adaptive PNC in OFDM systems operating over frequency-selective fading channels. Proposed and investigated are three methods to determine a common clustering for all subcarriers in order to reduce the overhead information required in the broadcast phase. The “Min-SER” method is given based on the analysis of the error event in the multiple access phase, while the “Max-fade-SER” and “Min-fade-distance” methods are recommended to further reduce the computational complexity in determining the common clustering. Considering the trade-off among performance, overhead and complexity, the “Max-fade-SER” method is the most attractive clustering method for applying adaptive PNC in OFDM systems.
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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 | 0.001 |
| Open science | 0.001 | 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".