A Semi-Numerical Analysis of Observations in Passive Tag-to-Tag Communications
Bibliographic record
Abstract
Radio Frequency Identification (RFID) is a rapidly growing technology that uses radio frequency signals to transfer data among devices.Recent works have proposed a novel reader-free RFID system where tags can communicate with each other directly with the existence of a continuous wave (CW) from some external RF carrier source or an ambient RF signal.In this paper, we propose the log-power difference as observations for the localization and tracking problems in passive Tag-to-Tag communication systems.The likelihood function of the log-power difference is derived in a seminumerical semi-analytical way.The proposed observation model is validated through estimating the distance between the two tags using maximum likelihood method.The results demonstrate the advantages of the modified method with multiphase backscattering where it shows a significantly improved estimation accuracy with more phases.The analysis is further extended to an infinite number of phases, where the maximum received power is obtained.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".