Energy-Efficient Joint User-RB Association and Power Allocation for Uplink Hybrid NOMA-OMA
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Bibliographic record
Abstract
In this paper, energy efficient resource allocation is considered for an uplink hybrid system, where non-orthogonal multiple access is integrated into orthogonal multiple access (OMA). To ensure the quality of service for the users, a minimum rate requirement is predefined for each user. An energy efficiency (EE) maximization problem is formulated by jointly optimizing the user clustering, channel assignment, and power allocation (PA). To address this problem, a many-to-one bipartite graph is first constructed considering the users and resource blocks (RBs) as the two sets of nodes. Based on swap matching, a joint user-RB association and PA scheme is proposed, which converges within a limited number of iterations. Moreover, for the PA under a given user-RB association, a feasibility condition is first derived. If feasible, a low-complexity algorithm is proposed, which obtains optimal EE for any successive interference cancellation (SIC) order and an arbitrary number of users. In addition, for the special case of two users per cluster, analytical solutions are provided for the two orders in which SIC can be implemented. These solutions shed light on how the power is allocated for each user to maximize the EE. Numerical results are presented, which show that the proposed joint user-RB association and PA algorithm outperforms other hybrid multiple-access-based and OMA-based schemes.
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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