PERFORMANCE ANALYSIS OF PF MAC SCHEDULER UNDER VARYING FEEDBACK DELAY IN LTE AND LTE-A EUTRAN
Bibliographic record
Abstract
Evolved Universal Mobile Telecommunications System (UMTS) Terrestrial Radio Access Network (EUTRAN) deals with high uplink and downlink throughput.The Proportional Fair (PF) Medium Access Control (MAC) scheduler offered a good balance between allocated resources and fairness among the User Equipment (UE) in comparison with other schedulers.In the PF scheduler, at each cycle of resource allocation, a feedback mechanism ensures that operational resource requirements are met while maintaining a degree of fairness among the UE.We analyze the effect of feedback Transmission Time Interval (TTI) delay on two typical EUTRAN networks, in terms of Key Performance Indicators (KPIs).One network is referred to as EUTRAN LTE and the other as EUTRAN LTE-A, which fulfils high throughput requirement.We evaluate the performance of the PF MAC scheduler for both networks under varying feedback delay in TTI.Simulated results show that the delay in TTI affects the performance of resource allocation in terms of throughput, fairness, and spectral efficiency.Feedback delay improves network performance by compensating effect of imperfect channel condition.
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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 | 0.005 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".