Bibliographic record
Abstract
Non-orthogonal multiple access (NOMA) is a promising multiple access scheme for Fifth Generation (5G) cellular networks as it provides a high spectral efficiency to meet the demands of new wireless applications, such as Internet-of-Things (IoT). Low density spreading (LDS) is a code-domain NOMA technique that spreads users' symbols with spreading sequences that contain a low number of nonzero chips. This low-density structure allows for detection using the belief propagation-based message passing algorithm (MPA). MPA is a suboptimum detector that converges to the optimum maximum a posteriori (MAP) detector with reduced complexity, but the algorithm complexity is exponentially proportional to the number of interfering users, which can be prohibitive when the system is operating near peak load. We propose an alternative detector based on the minimum mean square error (MMSE) and parallel interference cancellation (PIC) detectors which offer complexity that is quadratic to the number of users. Simulations show with a system load of 150%, the number of multiplications, additions and exponentials are reduced by 81.8%, 67.8% and 97.9% respectively with a penalty of about 0.25 dB at an error rate of 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-3</sup> .
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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".