A decorrelator based successive interference cancellation multiuser multirate receiver
Bibliographic record
Abstract
A new decorrelator based successive interference cancellation (DBSIC) multiuser Rake receiver is proposed for asynchronous variable processing gain (VPG) multirate code division multiple access (CDMA) systems over multipath Rayleigh fading channels. By including a decorrelator on top of matched filtering (MF) at each stage of the conventional successive interference cancellation (SIC) receiver to determine the user's signal for the next stage, DBSIC improves the overall system performance at the expense of feasible additional complexity. The simulation results show performance gains for DBSIC over the decorrelating and SIC detectors in the scenario of perfect channel estimation. While it is observed that the system performance degrades under imperfect channel side information, DBSIC consistently outperforms the decorrelating and SIC detectors. It is also shown that while the conventional cancellation/detecting order based on MF outputs outperforms random detecting order for both SIC and DBSIC under perfect or mild imperfect channel estimation, DBSIC performance is less sensitive to the detection ordering method than SIC
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".