Error performance of general order selection in correlated Nakagami fading channels
Bibliographic record
Abstract
A procedure for determining the probability distribution of the rth order statistic, Gr:L, r=1, 2, , L, among a set of L correlated Nakagami diversity branch gains G1, G2, , GL has been described in David and Nagaraja (2003) and Elkashlan et al. (2008). The results are used to evaluate the bit error rate (BER) of general order selection (GOS), a diversity method in which the rth order branch is selected for transmission, over correlated Nakagami fading branches. GOS can be used to improve system throughput and provide various levels of services, both of which are highly desirable in high-speed communication systems. Numerical and simulation results are presented and used to illustrate the effects of fading correlation on the BER associated with the rth order gain branch.
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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 | 0.000 |
| 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".