Cross-Layer Design and Analysis of Downlink Communications in Cellular CDMA Systems
Bibliographic record
Abstract
A cellular CDMA network with voice and data communications is considered. Focusing on the downlink direction, we seek for the overall performance improvement which can be achieved by cross-layer analysis and design, taking physical layer, link layer, network layer, and transport layer into account. We are concerned with the role of each single layer as well as the interaction among layers, and propose algorithms/schemes accordingly to improve the system performance. These proposals include adaptive scheduling for link layer, priority-based handoff strategy for network admission control, and an algorithm for the avoidance of TCP spurious timeouts at the transport layer. Numerical results show the performance gain of each proposed scheme over independent performance of an individual layer in the wireless mobile network. We conclude that the system performance in terms of capacity, throughput, dropping probability, outage, power efficiency, delay, and fairness can be enhanced by jointly considering the interactions across layers.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.004 | 0.002 |
| 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".