Increasing the DS/CDMA system reverse link capacity by equalizing the performance of different velocity users
Bibliographic record
Abstract
The capacity of the reverse link DS/CDMA system has been investigated by many researchers. Power control is essential for such systems to increase the capacity. Power control based on equalizing the received power levels from different users was proposed. The user's bit error rate (BER) depends on its received signal to noise ratio (SNR). Since the user's required SNR to achieve a given BER depends on its velocity, low mobility users are expected to have a lower BER compared to high mobility ones. Hence, the BER performance of a high mobility user is investigated when determining the system capacity. We propose a power control algorithm based also on power level measurements but where the required threshold is determined according to the user velocity where slow users thresholds are lower than fast ones. This results in increasing the slow users BER but lower the interference they cause to other users and hence increases the system capacity. This increase in capacity is found to be about 30% for a three resolvable Rayleigh fading paths channel and a path-loss exponent of four.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 0.001 |
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".