Combination of adaptive multiuser detection and parallel interference cancellation technique for DS-CDMA systems
Bibliographic record
Abstract
Two kinds of the adaptive multi-stage multiuser detectors are implemented for DS-CDMA. One is the adaptive MMSE/PIC multiuser detector and the other is the adaptive decorrelating/PIC multiuser detector. These detectors can be implemented by combining the adaptive multiuser detection schemes with the parallel interference canceller (PIC). From the simulation results and numerical calculation results, it is apparent the performance of the adaptive MMSE/PIC and the adaptive decorrelating/PIC detectors are very closed to that of the non-adaptive MMSE/PIC and nonadaptive decorrelating/PIC detectors. Also it was shown that the performance of these detectors is much better than that of the conventional detector and decorrelating multiuser detector and that they are near-far resistant. As the power of the interference increases the performance of MMSE/PIC and decorrelating/PIC approaches a single user bound. In addition, the adaptive algorithm does not require calculation of the cross-correlation and the inversion of the cross-correlation. Therefore, it is efficient to use the adaptive multiuser detectors instead of non-adaptive multiuser detectors it view of the system complexity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".