Packet detection for wireless networking with multiple packet reception
Bibliographic record
Abstract
A blueprint for an experimental low-power communications device (wireless mote) suitable for ad-hoc and networking applications is presented. The proposed device implements a random access packet-based communications protocol that exploits a special packet structure which is composed of separate header and payload portions. To enable robust packet detection, the headers consist of a preassigned spreading sequence which acts as a system access "key". The payload portion, on the other hand, utilizes a unique, packet-specific long spreading sequence to enable multi-packet reception (MPR), among other features. The packet header consists of W repetitions of a fixed spreading sequence, which are differentially encoded to provide immunity to unknown carrier frequency drifts. The receiver despreads the header and estimates the packet start time by differential coherent correlation before performing a threshold-based detection decision. Fixed-point simulation and FPGA measured results are provided for this the packet header detector and compared with the analytical packet-loss and miss probabilities. Near-far power loss experiments and analyses are discussed to demonstrate the feasibility of this receiver operating in wireless environments with large receive power variations.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".