Downlink resource allocation in cellular and multi-hop cellular CDMA systems
Bibliographic record
Abstract
A novel framework to model the problem of downlink resource allocation in conventional cellular systems and multi-hop cellular networks is presented. In conventional cellular CDMA systems, we use the dynamic pricing platform to formulate downlink resource allocation based on a novel defined cross-layer utility function. This utility function quantifies the degree of utilization of resources. Unlike the previous works, we solve the problem with the general objective of maximizing the total network utility instead of achieved utility of each Base Station (BS). In the second part of the thesis, we consider the problem of downlink resource allocation in multi-hop cellular networks where, using the concept of capacity regions, we propose an algorithm for joint optimum rate allocation and routing scheme in order to maximize the total throughput of multi-hop cellular CDMA networks. The notion of infeasibility factor is then defined and used to propose an adaptive scheme on top of the above algorithm to manage fundamental coverage-capacity tradeoff for the downlink.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".