Two-Way Amplify-and-Forward Relaying with Gaussian Imperfect Channel Estimations
Bibliographic record
Abstract
In this letter, we study the effect of channel estimation errors on the reception reliability of two-way relaying. For a network with two users that exchange information with each other through multiple amplify-and-forward relays, we investigate a single-relay selection scheme. Since the communication is two-way, the selection scheme aims at optimizing the worse performance of the two communication tasks between the pair of users. The signal-to-noise ratio (SNR) at the users' nodes of the relaying network is formulated and upper bounded. Then, the probability density function (PDF) of the upper bounded SNRs are determined. Subsequently, expressions for the error probabilities are obtained. Furthermore, an approximate PDF of the output instantaneous SNRs are derived, based on which simple and general asymptotic expressions for the error probabilities are presented and discussed. Numerical and simulation results are provided to verify the analysis and compare the performance of the two-way relaying network for different operating conditions and scenarios.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".