Bibliographic record
Abstract
Improvement of the capacity of the CDMA (code division multiple access) system is a major objective. The capacity of the system is mainly limited by the signal to noise ratio, where the noise comes from the channel background and from MAI (multiple access interference). Usually, the way to improve the capacity is to decrease the MAI; this is why orthogonal codes are adopted by the IS-95 standard. One problem is that the number of orthogonal codes is constrained by the dimensionality of the signal space. So in IS-95, there are only 64 orthogonal codes available when the number chips for each sequence is 64. To solve this problem, a non-orthogonal code called WBE (Welch bound equality) sequences (Massey and Mittelholzer 1991) is used in this paper The criterion to construct the code is to minimize the MAI. Two methods are used to construct the WBE sequences: from a linear cyclic code or from a Hadamard matrix. In order to improve the performance of the WBE sequence set, an iteration receiver (Sari et al. 1999) is applied. The conclusion obtained is that when the number of users is slightly greater than the signal space dimensionality, after the first iteration, the performance is only marginally worse than the orthogonal CDMA system.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".