Analysis of Delayed Acknowledgment Scheme with Packet Fragmentation of UWB-Based WPAN
Bibliographic record
Abstract
Delayed acknowledgment (Dly-ACK) and packet fragmentation are link-layer policies for ultra-wideband (UWB) based wireless personal area networks (WPANs) to improve the channel utilization, defined in both the IEEE 802.15.3a and ECMA-368 standards. On the other hand, the shadowing effect caused by people moving between the transmitter and receiver may severely degrade the received signal power and thus introduce channel variation. In this paper, we develop an analytical framework for studying the performance of the Dly-ACK and fragmentation over UWB fading channels. A Markov model is used to capture the time-variation of the UWB shadowing channel. The distribution of transmission delay of fragmented packets and the queuing behavior of the sender's buffer are derived. The system performance of packet delay and loss are obtained. Validated by simulations, the analytical results provide important insights and guidelines for better supporting high data rate, delay sensitive traffic in UWB-based WPANs.
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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 | 0.008 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".