Multiuser receivers that are robust to delay mismatch
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We investigate a new robust multiuser signal detector for asynchronous code-division multiple-access uplink channels under delay mismatch. We first formulate a robust decorrelating detector by dividing each user into two virtual users with rectangular chip pulse shapes. To increase the system capacity, a multistage version of the robust decorrelating detector is derived, which can achieve capacity of up to M/(M+1) of the spreading factor, where M is the observation block length. We further propose a robust successive interference cancellation (SIC) implementation. The proposed robust SIC detector adds only a residual error estimation procedure onto the standard SIC detector, so its computational complexity is of the same order of that of the SIC. Performance is investigated via analysis and simulation. Computer simulation results showed that our proposed robust SIC detector outperforms the conventional decorrelating detector when delay estimation error is present, and its performance is close to that of the decorrelating detector with perfect time-delay information. Finally, we generalize the robust SIC detector to the case of nonrectangular chip pulse shapes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.007 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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 it