Joint packet scheduling and dynamic base station assignment for CDMA data networks
Bibliographic record
Abstract
Abstract In current code division multiple access (CDMA) based wireless systems, a base station (BS) schedules packets independently of its neighbours, which may lead to resource wastage and the degradation of the system's performance. In wireless networks, in order to achieve an efficient packet scheduling, there are two conflicting performance metrics that have to be optimized: throughput and fairness. Their maximization is a key goal, particularly in next‐generation wireless networks. This paper proposes joint packet scheduling and BS assignment schemes for a cluster of interdependent neighbouring BSs in CDMA‐based wireless networks, in order to enhance the system performance through dynamic load balancing. The proposed schemes are based on sector subdivision in terms of average required resource per mobile station and utility function approach. The fairness is achieved by minimizing the variance of the delay for the remaining head‐of‐queue packets. Inter‐cell and intra‐cell interferences from scheduled packets are also minimized in order to increase the system capacity and performance. The simulation results show that our proposed schemes perform better than existing schemes available in the open literature. Copyright © 2007 John Wiley & Sons, Ltd.
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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 | 0.004 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".