Bibliographic record
Abstract
Spread spectrum multiple-access packetized wireless communications systems are considered. Although very efficient in low traffic (or low-rate) and low signal-to-noise ratio scenarios, the traditional and well-known spread ALOHA multiple access (SAMA) quickly collapses when both traffic and signal power increase. In certain situations, such as wireless sensor network traffic towards a sink, this severely limits the system data collection rates. Multi-packet reception (MPR), on the other hand, offers significant improvements in maximum throughput with respect to SAMA, whose performance is limited by the channel's collision mechanism. To enable MPR we propose to use multiple code CDMA, where different data packets are assigned individual (pseudo-random) spreading sequences. Several types of multiuser detector, such as the popular minimum mean-square error receiver are studied with respect to achievable system throughput and (system) power efficiencies. Due to the inherent asynchronicity of random access, we discuss asynchronous implementations of these receivers based on iterative cancelation processing. Basic queue behaviour utilizing a simplified MAC protocol, and analytical and numerical results are presented for a concept wireless sensor network with a central data collection sink, a setup that is also appropriate for last-mile relaying networks.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.005 | 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 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".