Multiuser detection with partial information for asynchronous CDMA-based radio networks
Bibliographic record
Abstract
We propose and evaluate a form of multiuser detector for base station reception in CDMA wireless. The setting we have in mind is one in which the interference at any base station has components whose parameters-power delay, signature sequence-are known to the receiver as well as components, representing out-of-cell transmissions, for example, whose parameters are unknown. The signals to be jointly decoded are thus to be extracted from a lager aggregate, plus noise, on the basis of partial parameter information. The setup provides a framework in which to study the impact of parameter information and detection group size on receiver performance. The proposed receiver architecture, amenable to adaptive as well as non-adaptive implementation, features a bank of linear equalizers at the input and a maximum-likelihood detector at the output; performance is described in terms of the mean-square error bit error rate and asymptotic efficiency. The computational complexity per bit, given the size of the detection group, is independent of the number of interferers.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 | 0.000 |
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 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".