Low-Complexity Multisampling Multiuser Detector for Time-Hopping UWB Systems
Bibliographic record
Abstract
Multiple access interference (MAI) in time hopping (TH) ultra-wideband (UWB) systems is known to be non-Gaussian. Much previous research in TH-UWB receiver design has attempted to propose better single-user UWB detectors by introducing more accurate models for the distribution of the MAI. Recently, it was shown that some of the single-user receivers track closely the optimum achievable single-user performance. Although, these receivers are simple, all suffer from error rate floors, and hence limited user capacity. Multiuser detection (MUD) is considered for offering high performance at the cost of complexity that grows exponentially with the number of users. Thought to be too complex for low-cost UWB receivers, MUD applied in TH-UWB systems benefits from the low duty cycle implying that the number of effective interfering users is small compared to the number of active users. A novel low-complexity multisampling multiuser detector inspired by the inferiority of single-user receivers and the small number of effective interfering users in TH-UWB systems is proposed. Simulation results show that this detector achieves the performance of the conventional matched filter receiver operating in a single-user system.
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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 | 0.000 |
| Open science | 0.000 | 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".