A Novel Approach for QoS-Aware Joint User Association, Resource Block and Discrete Power Allocation in HetNets
Bibliographic record
Abstract
We consider joint optimization of user-to-base-station (BS) association, and time-frequency resource block (RB) and power allocation in heterogeneous networks (HetNets). The objective is to develop a design: 1) that maximizes the number of users accommodated in the network while satisfying their quality of service demands and 2) that minimizes usage of the resources required to meet these demands. We investigate two novel instances of HetNets with opportunistic RB-reuse. In the first instance, user-to-BS associations and power allocations can be time-shared, and the RBs can be reused during the signaling interval. For this instance, it is shown that the design problem can be approximated by a problem that yields tight convex upper and lower bounds on the objective. In contrast, the second instance represents a case in which the RBs can be reused, but the user-to-BS associations and power allocations are not time-shared, and hence, fixed throughout the signaling interval. The latter case gives rise to a combinatorial optimization problem, which we provide an approximate solution for by using a polynomial-complexity two-phase approach based on semidefinite relaxation with randomization.
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How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".