Near-optimal resource block and power allocation mechanisms in uplink for LTE and LTE-Advanced
Why this work is in the frame
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Bibliographic record
Abstract
The Third Generation Partnership Project (3GPP) is playing a vital role in standardizing mechanisms for wireless broadband services through the Long Term Evolution (LTE) and LTE-Advanced (LTE-A) standards. In LTE and LTE-A, the resource allocation is scheduled and controlled by the base station (referred to as eNB) whose objective is to maximize the network performance. In this paper, we consider the uplink resource allocation problem in LTE and LTE-A with the objective of maximizing the total throughput of the cell, subject to the exclusivity, adjacency, clustering and power constraints arising from the use of Single Carrier Frequency Division Multiple Access (SC-FDMA) mechanism. We describe novel heuristic methods which can be adopted for both LTE and LTE-A to provide a near-optimal resource allocation using penalty-based optimization techniques. The simulation results show that our methods provide solutions which are more than 86% accurate when compared to the optimal solution.
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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 | 0.000 | 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 it