A Low-Power, High-Sensitivity, OOK-Super-Regenerative Receiver for WBANs
Bibliographic record
Abstract
A low power, high sensitivity, super-regenerative (SR) receiver for wireless body area networks (WBANs) is proposed in this brief. To enable high sensitivity while maintaining low power consumption, a two-step periodically quenching controller with automatic negative transconductance (-Gm) controller is designed for tuning the biasing current of the superregenerative oscillator (SRO) at twice the data rate of the input signal. To reduce the power consumption without compromising the loop gain, a novel cross-coupled SRO architecture using gm-boosting, adaptive bulk biasing, and dynamic threshold control techniques is presented. The proposed super-regenerative receiver with a center frequency of 2.4-GHz is implemented in 180-nm CMOS technology. Simulation results show that this receiver achieves a BER of 2 × 10-3at SNR = 12 dB and sensitivity of -87 dBm at 3.3 Mb/s while consuming 398 μW.
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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) | 0.001 | 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".