Optimal and simple near optimal non‐coherent detection in amplify‐and‐forward two‐way relaying over fast fading channels
Bibliographic record
Abstract
Two‐way relaying tends to become a celebrated technique in communication networks because of its unique characteristic in establishing a two‐step bilateral information exchange mechanism between users' pairs, as well as, arranging a virtual spatial diversity scenario. In this paper, two‐way relaying under amplify‐and‐forward strategy, and fast Rayleigh fading environment is considered. We investigate two distinct cases in which the relay retransmits users' superposed signals, either directly or after complex conjugation in two‐ or three‐phase modalities. We derive the optimal detection rule which is inherently computational complex. Two closed‐form suboptimal structures are proposed to circumvent this formidable problem. In the first form, we incorporate the destination noise into the relay counterpart, and assume Gaussian conditional distribution for the received signal in the latter. The first detector is designed using less stringent approximation and consequently has a better performance, whereas the second one benefits from a very low computational complexity and simple implementation and is more suitable for applications with strict computational and energy constraints such as sensor networks. Furthermore, we consider the imperfect self‐channel information case and extend the corresponding results. Bit error rate analyses and accompanying computer simulations show an improvement of about 5 dB over existing methods.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.000 | 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 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".