Low-complexity Optimal Scheduler for LTE Over LAN Cable
Bibliographic record
Abstract
Centralized Radio Access Network (C-RAN) is a promising architecture for handling complex interference scenarios generated by massive antennas that are anticipated in the next generation (5G) mobile networks. In conventional C-RANs, the fronthaul link between a Base Band Unit (BBU) and a Remote Radio Unit (RRU) deploys digital baseband signaling using an optical fiber link. Recently, copper-based analog fronthauls have been proposed as a low cost alternative to the fiber optics based fronthauls. These cable based fronthauls for a RAN, also known as Radio over Cable (RoC), leverage the existing LAN cable architecture to meet the high bandwidth requirements with almost negligible cost. In this paper, we propose an analog scheduler for mapping radio users over a LAN cable with multiple twisted pairs. More specifically, we discuss an LTE MISO based RAN and propose a user scheduler for allocating resources on the LAN cable. Through extensive numerical simulations, we show that a low complexity problem can be formulated to obtain quasi-optimal user schedules for LoC.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".