A distributed power and rate control scheme for mobile ad hoc networks
Bibliographic record
Abstract
The IEEE 802.11 Distributed Coordination Function (DCF) is the medium access protocol widely used for wireless local networks (LAN). Unfortunately, IEEE 802.11 DCF described in the standard faces some challenges when adopted for multi hop networks, which arise from the presence of the so-called hidden stations. This can cause degradation of the network throughput performance and energy consumption. Solving the hidden terminal problem will increase the possibility of the so-called exposed terminal and vice versa. In this paper, we present a novel scheme, called PRAS-CP ( transmission power and rate adaptive scheme with collision prevention), which enhances network performance through balancing the tradeoff between the hidden terminals and the exposed terminals. To accomplish this, PRAS-CP integrates the Physical/MAC attributes ( the carrier sensing range and the interference range) and carrier sensing mechanisms (PCS, VCS) to assign the appropriate data rate and transmission power values to successfully exchange the RTS/CTS DATA/ACK packets. Simulation results under different scenarios are used to demonstrate the significant throughput, energy gains, and fairness that can be obtained by PRAS-CP.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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 source (direct Gemma or distilled Codex), 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".