Bibliographic record
Abstract
We investigate a new robust multiuser signal detector for asynchronous code-division multiple-access uplink channels under delay mismatch. We first formulate a robust decorrelating detector by dividing each user into two virtual users with rectangular chip pulse shapes. To increase the system capacity, a multistage version of the robust decorrelating detector is derived, which can achieve capacity of up to M/(M+1) of the spreading factor, where M is the observation block length. We further propose a robust successive interference cancellation (SIC) implementation. The proposed robust SIC detector adds only a residual error estimation procedure onto the standard SIC detector, so its computational complexity is of the same order of that of the SIC. Performance is investigated via analysis and simulation. Computer simulation results showed that our proposed robust SIC detector outperforms the conventional decorrelating detector when delay estimation error is present, and its performance is close to that of the decorrelating detector with perfect time-delay information. Finally, we generalize the robust SIC detector to the case of nonrectangular chip pulse shapes.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".