A blind coherent spatiotemporal processor of orthogonal Walsh‐modulated CDMA signals
Bibliographic record
Abstract
Abstract A more efficient detection of orthogonal Walsh‐modulated Code Division Multiple Access (CDMA) signals is required not only for better exploitation of current IS‐95 CDMA systems but also for future cdma2000 3G networks. Integration of adaptive antennas at the base station has been recognized as one key lever to increasing capacity and spectrum efficiency. Prospective array‐receiver solutions such as the 2‐D‐RAKE improve performance; however, in the absence of a pilot signal, they have to implement noncoherent detection. In this work, we propose a space‐time processor that achieves coherent detection of orthogonal Walsh‐modulated CDMA signals without a pilot. We assess its performance in spatially correlated Rayleigh‐fading. Simulation results for voice links of 9.6 Kbps indicate that up to an antenna‐correlation factor of 0.8, the proposed receiver outperforms the conventional 2‐D‐RAKE's capacity by 90% in nonselective fading. This gain shrinks fast at higher correlation factors. In selective fading, however, it maintains about a 130% gain in capacity over the entire correlation range. For data links of 153.6 Kbps, this performance advantage increases up to 180–200%. With high‐speed mobiles, however, it vanishes quickly at correlation factors beyond 0.5. Overall, the capacity gains of the proposed spatiotemporal receiver structure increase with reduced relative Doppler (Doppler‐frequency/symbol‐rate ratio). This may arise from increased spatiotemporal diversity, higher transmission rates, and/or slower mobility. Copyright © 2002 John Wiley & Sons, Ltd.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".