Performance comparison between the use of group signatures and robust error correction codes in wireless multiuser communication systems
Bibliographic record
Abstract
We investigate the performances of two wireless multiuser space-time block coding (STBC) communication systems. In the first system, the notion of group signature (GS) proposed by Tran and Sesay (see IEEE Vehicular Technology Conference (VTC2002-Spring), Alabama, USA, May 2002) is applied and in the second system, all users communicate on the same channel and no GS is used. In both systems, a 4-state convolutional code is concatenated with the space-time block code proposed by Alamouti (see IEEE J. Select. Areas Commun., vol.16, no.8, p.1451-58, 1998). In the second system, the bandwidth allocated to the use of GS in the first system is allocated for the use of a stronger convolutional code such that both systems utilize the same bandwidth. Computer simulation results show that the first system, with the use of GSs, significantly outperforms the second system in the region of low signal-to-noise ratios, at the same hardware and computational complexities.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".