Adaptive Multistage Detection for DS-CDMA Systems in Multipath Fading Channels
Bibliographic record
Abstract
We propose an adaptive multistage detection scheme with low complexity for direct-sequence code-division multiple-access (DS-CDMA) systems in the presence of flat and frequency-selective fading. The first stage consists of a blind adaptive multiuser detector based on the linear constrained minimum variance (LCMV) criterion. The interference cancellation (IC) occurs in the second stage. The performance of the proposed iterative detector over both flat and frequency-selective fading channels is investigated and compared to the single-user bound. In all cases, the proposed iterative receiver is shown to offer a substantial performance improvement and a large gain in user capacity relative to the standard LCMV. In flat fading channels, our results show that the performance of the proposed detector is very close to the single-user bound. On the other hand, the performance of the iterative receiver over frequency-selective channels is noted to be in the order of 1 dB far from the single-user bound.
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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 | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 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".