An Ultra-Low-Power Low-Voltage WuTx With Built-In Analog Sensing for Self-Powered WSN
Bibliographic record
Abstract
This paper presents an ultra-low-power, low-voltage wake-up transmitter (WuTx) capable of transmitting two sensors' analog output simultaneously using short pulses that their LOW and HIGH time are modulated with the analog inputs. A subthreshold relaxation oscillator along with an ultra-low-power comparator and voltage reference creates a baseband signal modulated based on two input analog signals, a ring oscillator upconverts the baseband signal to the desired transmission channel frequency (915 MHz or 2.4 GHz), and finally, an efficient Class E power amplifier with variable output power drives the antenna. The minimalist design of the proposed transmitter avoiding power-hungry data converters for sensor readout circuitry and modulation, short pulses at the output that enable the power amplifier for a short time during transmission along with the operation in the subthreshold region significantly reduces the overall power consumption. The proposed low-power and low-voltage transmitter is ideal for the long-term deployment of self-powered wireless sensors when the voltage gain and efficiency of harvesters are limited. Fabricated in a 65nm standard TSMC CMOS process, the proposed transmitter consumes a minimum of 5.41μW average power when it is on while delivering the output power of -1dBm and 7nW when it is completely off.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".