Finger Replacement Method for Rake Receivers in the Soft Handover Region
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Bibliographic record
Abstract
We propose and analyze a new finger replacement technique that is applicable for RAKE receivers in the soft handover (SHO) region. More specifically, the receiver uses in the SHO region by default the strongest paths from the serving base station (BS) and only when the combined signal-to-noise ratio falls below a certain pre-determined threshold, the receiver uses more resolvable paths from the target BS to improve the performance. Instead of changing the configuration for all fingers, the receiver just compares the sum of the weakest paths out of the currently connected paths from the serving BS with the sum of the strongest paths from the target BS and selects the better group. Using accurate statistical analysis, we investigate in this letter the tradeoff between error performance, average number of required path comparisons, and SHO overhead offered by this newly proposed scheme.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.006 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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