Optimal ACK mechanisms of the IEEE 802.15.3 MAC for ultra-wideband systems
Bibliographic record
Abstract
Ultra-wideband (UWB) transmission is an emerging wireless technology for future short-range indoor and outdoor multimedia applications. To coordinate the access to the wireless medium among the competing devices, the IEEE 802.15.3 medium access control (MAC) is proposed for short-range high-speed wireless personal area networks (WPANs) in the IEEE 802.15.3a task group. In the MAC, three acknowledgment (ACK) mechanisms are adopted during channel time allocation for error control over the error-prone wireless channel: No-ACK, Immediate-ACK (Imm-ACK), and Delayed-ACK (Dly-ACK). Frames received with errors can be retransmitted in the Imm-ACK and Dly-ACK mechanisms. However, how to optimally use these ACK mechanisms during channel time allocation is still an open issue. In this paper, we investigate how to configure the ACK mechanism parameters in order to achieve optimal throughput performance. We first formulate the throughput optimization problem for a contention-free channel time allocation under error channel condition. We then apply the three ACK mechanisms in the contention access period, to optimize the channel throughput. Simulation results demonstrate the effectiveness of our investigation.
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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 | 0.004 | 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 | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".