Call-level and packet-level performance modeling in cellular CDMA networks
Bibliographic record
Abstract
We present a queueing analytical model to evaluate call-level and packet-level performances for uplink transmission of data calls in a voice/data cellular CDMA network. In the call-level, call admission control (CAC) is used to ensure that the cell is not overloaded and also to prioritize the handoff calls over the new calls. We assume finite queueing at the mobile to buffer the data packets for uplink transmission. The transmission rates for data calls can be adjusted to accommodate more voice and/or data calls while satisfying a minimum signal-to-interference (SIR)/rate requirement for voice/data calls. Call-level performance measures (i.e., new call blocking and handoff call dropping probabilities) for both voice and data calls and packet-level performance measures (i.e., queue throughput, packet dropping probability and delay) specifically for data calls can be obtained from our model. Impacts of the call-level parameter settings on the packet-level performance measures are investigated and typical numerical results are presented
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".