Energy efficiency of resource scheduling for non-orthogonal multiple access (NOMA) wireless network
Why this work is in the frame
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Bibliographic record
Abstract
Non-orthogonal multiple access (NOMA) is a promising technique for the fifth generation mobile communication due to its high spectrum efficiency. By applying superposition coding and successive interference cancellation techniques, multiple users can be multiplexed on the same subchannel in NOMA systems. Previous works focus on subchannel and power allocation to maximize the sum rate; however, the energy-efficient resource allocation problem has not been studied for NOMA systems. In this paper, we aim to optimize subchannel assignment and power allocation to maximize the energy efficiency for the downlink NOMA network. Assuming perfect knowledge of the channel state information at base station, we propose low-complexity suboptimal algorithms which include subchannel assignment and power allocation for subchannel users. In the power allocation scheme, difference of convex functions programming approach is exploited to transform and approximate the original optimal problem into a convex optimization problem. Simulation results show that our proposed algorithms yield much better improvements than orthogonal frequency division multiple in terms of sum rate and energy efficiency.
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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 | 0.001 | 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