A Low Power Frequency Tunable FSK Receiver Based on the N-Path Filter
Bibliographic record
Abstract
This brief presents a low power frequency tunable frequency shift keying (FSK) receiver based on N-path filter. The N-path filter serves as the first stage of the receiver and converts the frequency difference between two tones to amplitude difference. To evaluate the maximum achievable data rate of the proposed receiver, we studied the behavior of N-path filter under two-tone input condition. With linear periodically timevariant theory, the equations for transient response between two tones are derived for differential two-port N-path filters and verified by the simulation. Based on the analysis, an optimum data rate is obtained for the proposed N-path filter-based FSK receiver. Implemented in 0.13-μm CMOS process, the chip occupies 300 × 700 μm2, achieves data rate of 2.5 Mb/s, and 74 pJ/bit energy per bit at -65 dBm sensitivity. Frequency tuning is also demonstrated.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".