Analysis of multi‐user detection of multi‐rate transmissions in multi‐cellular CDMA
Bibliographic record
Abstract
Abstract In this paper, we address the issue of multi‐user receiver design in realistic multi‐cellular and multi‐rate CDMA systems based on performance analysis. We consider the multi‐user detection (MUD) technique, denoted interference subspace rejection (ISR), because it offers a wide range of canonic suppression modes that range in performance and complexity between interference cancellers and linear receivers. To further broaden our study, we propose a modified ISR scheme called hybrid ISR to cope better with multi‐rate transmissions. The performance analysis, which is based on the Gaussian assumption (GA) and validated by simulations, takes into account data estimation errors, carrier frequency mismatch, imperfect power control, identification errors of time‐varying multipath Rayleigh channels and intercell interference. This analysis enables us to optimize the selection of the MUD mode for multi‐rate transmissions in different operating conditions. The effectiveness of interference cancellation is indeed investigated under different mobile speeds, numbers of receiving antennas, near‐far situations, channel estimation errors, and out‐cell to in‐cell interference ratios. This investigation suggests that the out‐of‐cell interference, the residual in‐cell interference, the noise enhancement as well as low mobility favor the simplest MUD modes as they offer the best performance/complexity tradeoffs. Copyright © 2008 John Wiley & Sons, Ltd.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".