Performance of Maximal Ratio and Optimum Combining with Channel Estimation Errors and Multiple Interferers in Rayleigh Fading Channels
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Bibliographic record
Abstract
This paper analyzes the performance of maximal ratio combining (MRC) and compares it with the performance of optimum combining (OC) in the presence of channel estimation errors and multiple interferers in a flat Rayleigh fading environment. The probability density function (PDF) of the signal-to-interference-plus-noise ratio at the output of the maximal ratio combiner has been derived in prior work, assuming Gaussian channel estimation errors. We use that PDF to derive analytical expressions for a number of important performance measures such as the outage probability and the average bit error probability for different modulation formats in interference-limited systems. These expressions are used to show that the simpler MRC method can outperform the more complex OC receiver when the channel estimator performs poorly, and quantify the threshold of correlation between the true and estimated channels at which the cross-over occurs.
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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 it