A new algorithm to reduce the deviation in the base stations transmitted powers during soft handoff in CDMA cellular systems
Bibliographic record
Abstract
Soft handoff (SHO) is one of the critical components that determine the performance of a CDMA cellular system. The mobile station in 3G systems send power control commands to the base stations to adjust their powers. These power control commands can be received in error by on of the base stations in the active set serving the mobile. This results in the base stations transmitted powers deviating. Reducing the deviation in the base stations transmitted powers helps to achieve the desired diversity gain from SHO. We propose to change the way the base stations respond to power control commands. This does not require changing the way the mobile issues the power control commands. From the simulation results we see that at a speed of 5 km/h, the probability that the difference in the two base stations transmitted powers being greater than 5 dB is about 25% using the conventional scheme while it is only 8% for the proposed scheme (majority voting over two commands). We notice also that the base stations average transmitted power is reduced by employing the majority voting scheme.
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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 | 0.002 |
| 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 | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".