Performance of parallel interference cancellation in large CDMA over a fading channel
Bibliographic record
Abstract
The paper introduces an analytical tool to find the large-system performance of a multistage linear partial parallel interference cancellation (PPIC) receiver using the moments of the eigenvalues of the covariance matrix for a code division multiple access (CDMA) system over a frequency-flat fading channel. The figure of merit to evaluate the performance is the signal-to-interference-plus-noise ratio (SINR) that is calculated under a large-system condition. In this case, the number of active users and the processing gain tend towards infinity while their ratio is a fixed value. It is shown that the large-system performance is a function of the system load, the partial cancellation factor (PCF), the number of interference cancellation stages, the signal-to-noise ratio (SNR), and the received powers of the interfering users. Furthermore, for practical applications, the physical meaning of the large system is described by numerical simulations.
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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 | 0.000 | 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 | 0.001 |
| 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".