The information theoretic reliability function for multipath fading channels with diversity
Bibliographic record
Abstract
With the emergence of wireless and mobile communication systems and technology new channel models and impairment phenomena have appeared. We derive the information theoretic reliability function for a number of ideal fading channels with diversity. It has been shown by Buz (see Ph.D. Dissertation, Dept. of Elec. and Comp. Eng., Queen's University, Kingston) that the asymptotic SNR loss in the capacity, relative to the AWGN channel, for ideal Rayleigh fading is no more than 2.51 dB, which is not very dramatic. By looking at the reliability function, we have found, on the other hand, that the loss in the cutoff rate due to Rayleigh fading is monotonically increasing with SNR and considerably longer codes are required for transmission over the Rayleigh channel at rates below capacity. Nevertheless, this loss can be regained by means of diversity, where it has been found that most of the loss can be reclaimed with the use of 2 or 3 antennas.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".