Adaptive multistage parallel interference cancellation for CDMA
Bibliographic record
Abstract
An adaptive multistage parallel interference cancellation technique based on the partial interference cancellation (IC) approach of Divsalar and Simon (see Tech. Rep. 95-21, JPL Publication, 1995) was proposed by Xue, Weng, Le-Ngoc and Tahar (see Proc. of VTC'SS, Vancouver, Canada, 1999) for multipath fading channels. In this paper, the proposed technique is applied to develop a receiver structure in an AWGN environment. Unlike the scheme of Divsalar et al., the weighting factors in this proposed scheme are derived by minimizing the mean-square error between the received signal and its estimate through an LMS algorithm. Neither training sequence nor pilot signal is needed. The complexity of the proposed adaptive multistage PIC structure is much lower than that of linear multiuser detectors. Simulation results show the superior performance of the proposed receiver structure over an AWGN channel and in various conditions.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".