Two-Way Amplify-and-Forward Relaying with Gaussian Imperfect Channel Estimations
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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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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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