Transmit Antenna Selection Strategies for Cooperative MIMO AF Relay Networks
Bibliographic record
Abstract
In this paper, an analytical framework is developed for the performance analysis of three transmit antenna selection (TAS) strategies for dual-hop multiple-input multiple-output channel-assisted amplify-and-forward (CA-AF) relay networks over Rayleigh fading. The cumulative distribution function of a lower bound of the end-to-end signal-to-noise ratio (SNR) of the optimal TAS strategy is derived and used to obtain the upper bounds of the outage probability and the average symbol error rate (SER). The exact moment generating functions (MGFs) of the end-to-end SNR of two suboptimal TAS strategies are also derived for the ideal CA-AF MIMO relay networks. These MGFs are then used to present accurate and efficient closed-form approximations to evaluate the outage probability and average SER. Numerical and Monte-Carlo simulation results are provided to analyze the performance of the system and to verify the accuracy of our analytical framework.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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 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".