Protective Dummy-byte Preamble Padding for improving ZigBee packet transmission under Wi-Fi interference
Bibliographic record
Abstract
Recent studies have shown that the low-power ZigBee based wireless sensor networks (WSN) are vulnerable to the interference generated by nodes of Wi-Fi wireless local area networks (WLAN). Mutual interference can be mitigated at nodes of either technology when energy detection (ED) is enabled in clear channel assessment (CCA). From our experimental studies on ZigBee and Wi-Fi coexistence issue, it is determined that a significant amount of ZigBee packet losses occur due to the Wi-Fi interference induced corruption of the physical layer header of ZigBee packets, which could happen even when the ED mechanisms of the Wi-Fi and ZigBee devices are able to detect each other's signal and CSMA/CA algorithms are applied accordingly. To study this phenomenon, a series of experiments were carried out, followed by thorough analysis of the recorded data. The study led to the design of a simple but effective technique named Protective Dummy-byte Preamble Padding (PDBPP) that improves the performance of ZigBee packet transmission in terms of packet loss rate (PLR) and transmission efficiency. The experimental performance evaluation results confirmed the effectiveness of PDBPP in improving PLR and transmission efficiency of a ZigBee network exposed to interference generated by collocated WLAN. Some material in this paper is part of a pending patent.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".