Chip-locked space-time filtering for maximizing SINR in asynchronous DS-CDMA systems
Bibliographic record
Abstract
This paper considers a chip-locked space-time (CLST) filtering technique for direct-sequence code-division multiple access (DS-CDMA) systems. CLST filtering exploits the knowledge of the multiple access interference (MAI) chip delays, as well as the fact that the MAI spectrum is colored in the time and space domains. Chip delays of interferers from the same cell as the desired user are available at the base station and can be used to improve performance of single-user receivers. CLST filtering reduces MAI through joint optimization of spatio-temporal filtering and exploitation of chip delays of locked interference, without the need of interferers spreading codes. A significant improvement in signal-to-interference plus noise ratio can be achieved through CLST filtering with respect to the case when the interference is unlocked. The capabilities of CLST filtering to suppress chip-delay-locked interference improves with increasing chip waveform excess bandwidth. Numerical results show that CLST filtering already provides significant performance gains with square-root raised cosine chip pulses of small excess bandwidth. Furthermore, it is also shown that CLST filtering for a long observation interval is suitable for DS-CDMA systems employing long sequence spreading.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.005 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".