Non-orthogonal CDMA forward link offers flexibility without compromising capacity
Bibliographic record
Abstract
We proposed the use of non-orthogonal CDMA forward link in future micro-cellular multi-media CDMA systems. It allows the use of mobile-transparent hand-off, a hand-off method which does not require sending a control signal to a mobile for its initiation. This reduces the hand-off related signaling overhead, therefore makes non-orthogonal forward links well suited to micro-cellular systems where there will be frequent hand-offs. Comparing with orthogonal forward links, it also allow much more flexibility in data rates and channel coding rates, hence readily accommodate high bit rate or VBR services. In addition, the possibility of using low-rate error control codes in non-orthogonal links provides a way to compensate for the loss in capacity due to non-orthogonality. Simulation results show that when the flexibility in error control coding is exploited, orthogonal and non-orthogonal forward links have comparable capacities in Rayleigh fading channels. In static channels (or very slowly fading Rician channels), orthogonal forward links have higher capacities, but the capacities of non-orthogonal forward links are not much worse than those of orthogonal forward links when the path loss exponent is small.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".