Indoor wireless reception improvement using cross-polarized multipath signals
Bibliographic record
Abstract
Previous work has noted the distinct characteristics of vertically and horizontally polarized multipath components for indoor non-line-of-sight (NLOS) environments. Using measured data, the receiver signal-to-noise ratios (SNRs) for coherent and noncoherent combining of the co- and cross-polarized multipath components are compared to those obtained with omnidirectional reception for vertical or horizontal polarizations. It is seen that significant improvements in SNR can be achieved using intelligent combining with polarization diversity. Furthermore, it is observed that when the receiver is unable to resolve multipath components, coherent combination of both orthogonally polarized signals components provides a consistent advantage over vertically or horizontally polarized omnidirectional reception. At higher bandwidths, the increased resolution improves the performance of all techniques however the dual polarization multipath combining retains its relative advantage over the other techniques.
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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 | 0.001 | 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".