Effective channel assignment in multi-hop W-CDMA cellular networks
Bibliographic record
Abstract
Multi-hop relaying is an important concept in tackling the inherent problems of limited capacity and coverage in cellular networks. It helps to solve the dead-spots problem and to ease congestion in hotspots. However, to obtain good performance of multi-hop relaying, an effective channel assignment scheme is needed. In this paper, we study the design goals of a good channel assignment scheme. We then propose a channel assignment scheme, called Extended Delay-Sensitive Slot Assignment (E-DSSA), which achieves all these goals. The distinctive feature of E-DSSA is the use of a novel transmission zone testing technique which allows high flexibility and precision in channel assignment in TDD W-CDMA multi-hop cellular environment. Performance evaluation shows that E-DSSA outperforms its existing counterparts in terms of data throughput with low delay for both sparse and dense networks. E-DSSA is also shown to adapt to different cell sizes achieving high throughput and call acceptance ratios.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".