Energy-Efficient Cross-Layer Resource Allocation for Heterogeneous Wireless Access
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, an uplink cross-layer resource allocation problem based on imperfect channel state information (CSI) is modeled as min-max fractional stochastic programming for heterogeneous wireless access. The resource allocation is subject to constraints in delay, service outage probability, system radio bandwidth, and total power consumption. The joint bandwidth and power allocations are based on CSI at the physical layer and queue state information (QSI) at the link layer. In order to determine the transmission rate of each mobile terminal according to the queue buffer occupancy, a probability upper bound of exceeding the maximum packet delay in terms of a required transmission rate is presented based on M/D/1 model. Then, the bandwidth and power allocation problem is transformed into bi-convex programming, and an optimal distributed bandwidth and power allocation algorithm is proposed. To reduce computational complexity, a suboptimal distributed bandwidth and power allocation algorithm is presented. Simulation results demonstrate that the proposed algorithms improve the energy efficiency greatly.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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 it