Joint Relay and Destination Design for Two-Way MIMO AF Multi-Relay Systems
Bibliographic record
Abstract
In this paper, we propose a joint relay and destination optimization design for two-way half-duplex amplify-and-forward (AF) relay systems with multiple relays, each with multiple antennas. By using the sum mean-squared error (MSE) criterion and Wiener filtering principle, the joint relay and destination design is formulated as an optimization problem of the relay precoding matrix under the constraint of total relay transmit power. Then, constructing a virtual point to point MIMO channel and using the singular-value-decomposition (SVD), the optimization problem is simplified to a convex minimization of an upper bound of the sum MSE through a diagonalization process. Finally, a suboptimum scheme is proposed to solve the simplified convex optimization problem. Monte-Carlo simulation shows that the proposed suboptimal scheme gives a better MSE performance than the existing gradient descent algorithm does, and moreover, our method becomes more advantageous when the number of relays or the number of relay antennas increases.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".