Linear Precoders for OSTBC Mimo Systems with Correlated Rayleigh Fading Channels Based on Convex Optimization
Bibliographic record
Abstract
In this paper, we present a precoder design framework and a computationally simple precoding technique for OSTBC based MIMO wireless systems with both transmit and receive correlations for the case of Rayleigh fading. It is assumed that the correlation among receive antennas is independent of the correlation among transmit antennas (and vice versa). The transmit and receive correlation matrices are assumed to be available at the transmitter, while the instantaneous channel state information (CSI) is unknown. The proposed precoder minimizes the upper bound on the symbol error rate (SER). Our main contribution consists of developing a convex formulation for originally non-convex problem of SER minimization for precoder design. Additionally, it can be shown that previously known solutions for some special cases of precoder design naturally follow from our more general results. Numerical simulations illustrate the improved performance of the proposed precoders in terms of the output SER.
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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 | 0.000 |
| Open science | 0.000 | 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".