Multiple Access Computation Offloading for the K-User Case
Bibliographic record
Abstract
When multiple users seek to offload computational tasks to their access point, the nature of the multiple access scheme, and the optimization of its parameters, play a critical role in the system performance. For a system with heterogeneous tasks, we adopt a time-slotted signaling structure in which different numbers of users transmit in each slot, subject to individual power constraints. We consider the problem of optimizing the rates and powers of the users transmitting in each time slot, and the time slot lengths, so as to minimize the energy expended by the users. For time-division multiple access (TDMA) and "rate optimal" multiple access, we obtain reduced-dimension convex formulations, while for (suboptimal) non-orthogonal multiple access (NOMA) with independent decoding (ID) or fixed-order sequential decoding (FOSD), we develop a successive convex approximation algorithm with feasible point pursuit. These formulations are then embedded in a customized tree search algorithm for the set of offloading users. Our results demonstrate how the NOMA-FOSD schemes bridge the performance gap between TDMA and the rate-optimal schemes.
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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 | 0.000 | 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 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".