Bibliographic record
Abstract
Many investigations of hybrid selection (HS) diversity assume maximal ratio combining (MRC) of the selected branches. However, a coherent detector needs to dwell on the received signal for some time before it can produce accurate channel estimates for fading compensation, a requirement that appears inconsistent with the branch switching that occurs in a selection diversity receiver. Motivated by this observation, we derive in this letter analytical results on the switching rate and average dwell time of a selection diversity receiver where M out of a total of N independent branches are selected for combining. We show that the switching rate can be many times the Doppler frequency, while the average dwell time can be a small fraction of the reciprocal Doppler frequency. The brevity of the dwell times suggests difficulty in obtaining channel state information, which in turn calls into question performance analyses of idealized HS/MRC structures. Our results also suggest that HS/MRC should be frame-based, rather than continuously acting in time
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".