Joint beamforming and antenna selection for two-way amplify-and-forward MIMO relay networks
Bibliographic record
Abstract
A novel joint beamforming and antenna selection strategy is proposed and analyzed for two-way multiple-input multiple-output amplify-and-forward relay networks. Specifically, this strategy selects the optimal transmit precoding and receiver filtering vectors at the two source terminals, and an optimal transmit/receive antenna at the relay terminal based on minimizing the overall outage probability. The performance of this transmission strategy is quantified by first deriving the exact cumulative distribution function of the effective signal-to-noise ratio (SNR), and thereby, evaluating the overall outage probability, its asymptotically exact high SNR approximation and achievable diversity order. For a multiple relay scenario, a joint relay, beamforming, and antenna selection strategy is proposed and analyzed as well. Interestingly, our selection strategies are optimal in the sense of the overall outage probability, and hence, in the sense of achievable diversity order as well.
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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 | 0.001 |
| 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) | 0.001 | 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".