Time and power scheduling in an ad hoc network with bidirectional relaying and network coding
Bibliographic record
Abstract
Network coding NC is a technique that allows intermediate nodes to combine the received packets from multiple links and forwarded to subsequent nodes. Compared with pure relaying, using NC in a wireless network, one can potentially improve the network throughput, but it increases the complexity of resource allocations as the quality of one transmission is often affected by the transmission conditions of multiple links. In this paper, we consider an ad hoc network, where all the links have bidirectional communications, and a relay node forwards traffic between the source and the destination nodes using NC. All transmissions share the same frequency channel, and simultaneous transmissions cause interference to each other. We consider both digital NC and analog NC strategies, referred to as DNC and ANC, respectively, and schedule transmission time and power of the nodes in order to maximize the overall network throughput. For DNC, an optimum scheduling is formulated and solved by assuming that a central controller is available to collect all the link gain information and make the scheduling decisions. Distributed scheduling schemes are proposed for networks using DNC and ANC. Our results indicate that the proposed scheduling scheme for DNC achieves higher throughput than pure relaying, and the scheduling scheme for ANC can achieve higher throughput than both DNC and pure relaying under certain conditions. Copyright © 2013 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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".