A call admission control scheme for packet data in CDMA cellular communications
Bibliographic record
Abstract
In wireless cellular communication systems, call admission control (CAC) is to ensure satisfactory services for mobile users and maximize the utilization of the limited radio spectrum. In this paper, we propose a new CAC scheme for a code division multiple access (CDMA) wireless cellular network supporting heterogeneous self-similar data traffic. In addition to ensuring transmission accuracy at the bit level, the CAC scheme guarantees service requirements at both the call level and the packet level. The grade of service (GoS) at the call level and the quality of service (QoS) at the packet level are evaluated using the handoff call dropping probability and the packet transmission delay, respectively. The effective bandwidth approach for data traffic is applied to guarantee QoS requirements. Handoff probability and cell overload probability are derived via the traffic aggregation method. The two probabilities are used to determine the handoff call dropping probability, and the GoS requirement can be guaranteed on a per call basis. Numerical analysis and computer simulation results demonstrate that the proposed CAC scheme can meet both QoS and GoS requirements and achieve efficient resource utilization.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| 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".