Power efficient multicasting for pre‐cached multiple description traffic in a wireless network
Bibliographic record
Abstract
Abstract In this paper, we study multicasting multiple description traffic to a group of mobile stations (MSs). The traffic is pre‐cached at a number of access points (APs), and the MSs have different quality requirements in terms of number of required descriptions. Each AP transmits one description and forms a single‐hop multicast group to reach a certain number of MSs. Different APs can transmit the same or different descriptions. MSs requiring multiple descriptions should be covered by at least the same number of the APs that transmit different descriptions. We study two problems, description assignments, and power allocations. The former is to assign a description for each AP, and the latter is to allocate the transmission power for each AP. Two objectives are considered subject to satisfying the requirements of the MSs, one is to minimize the total transmission power of all the APs, and another is to minimize the maximum transmission power of the APs. For each objective, a centralized and a distributed scheme are proposed, and their performance is compared with the optimum. Numerical results show very good performance of the heuristic schemes. Copyright © 2016 John Wiley & Sons, Ltd.
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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 | 0.001 | 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 | 0.001 |
| 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".