Throughput Maximization via Joint Optimization of Fronthaul and Access Links in C- RANs
Bibliographic record
Abstract
This paper addresses the problem of sub-carrier and user association in a downlink cloud based radio access network (C- RAN), considering fronthaul and access radio frequency (RF) links and orthogonal frequency division multiple access (OFDMA). Our problem is most relevant to scenarios where bandwidth resources must be shared between the fronthaul and access links. In order to assign users to their appropriate cells and to allocate frequency resources, we maximize the sum throughput. Importantly, we consider fronthaul and inter-cell interference. The resulting optimization problem is based on joint fronthaul and access frequency resource allocation and user association and is non-convex. To tackle the non-convexity of the problem, a successive convex approximation method is proposed. In order to guarantee integer solutions, we introduce a term, called virtual interference, into the problem formulation. Numerical results validate the effectiveness of proposed algorithm in jointly allocating resources of fronthaul and access links. The results confirm improved total network throughput by considering full interference scheme and sharing resources between fronthaul and access links.
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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 | 0.001 |
| Open science | 0.000 | 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".