Single-carrier equalization and distributed beamforming for asynchronous two-way relay networks
Bibliographic record
Abstract
In this paper, we consider a single-carrier communication scheme, where two transceivers exchange information with the help of multiple relays. The propagation delay in each relaying path is assumed to be different from those of the other paths. As such, the end-to-end channel is frequency selective, and hence, it produces inter-symbol-interference (ISI) at the two transceivers. The simple amplify-and-forward scheme is used at the relays and channel equalization is employed at both transceivers to combat ISI. We minimize the mean square error (MSE) of the total estimated received signals at the both transceivers, subject to a total power budget constraint, by optimizing the channel equalizers, the relay beamforming weights, and the transceivers' powers. We show that our proposed approach leads to a relay selection method which transforms the end-to-end channel into a frequency flat channel. We also present a semi-closed-form solution for the optimal relay beamforming weight.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".