Error rate analysis of asynchronous multicode DS-CDMA systems
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A precise bit-error probability analysis method is derived for a multicode DS-CDMA system in an additive white Gaussian noise channel. The method is applicable to a multicode DS-CDMA system with an arbitrary number of multiple code sequences and any selection of multiple code sequences. The precise method gives results that discriminate the effect of the selection of multiple code sequences on the bit-error probability, whereas Gaussian approximations do not. Thus, the new method can be used to select the best multicode set for a given system, a task that cannot be achieved using Gaussian approximations. A two-step analytical procedure enables deriving an explicit, compact form for the characteristic function of the receiver decision statistic in a DS-CDMA system with an arbitrary number of multiple code sequences, and for any selection of multiple code sequences.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.011 | 0.002 |
| 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