Extending the Dynamic Range of Square-Law Power Detectors for Large-Scale Receiver Arrays
Bibliographic record
Abstract
This letter proposes and investigates a solution to extend the compression point (P1dB) and dynamic range (DR) of square-law power detectors. A nonlinear driver stage is incorporated before the detector to compensate for the detector’s <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">I</i>–<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">V</i> curve nonideality, enabling distortion-free mixing over a wider range of input RF signals. The modified MOSFET-based detector demonstration achieves a 14-dB increase in P1dB, raising the baseline from −10 to over 4 dBm while maintaining a bias current consumption of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$5~\mu $</tex-math> </inline-formula>A. An off-the-shelf BJT proof-of-concept verification shows an 11-dB P1dB extension, reaching 0 dBm. The enhanced performance, combined with its compatibility with integrated circuit (IC) implementation and low-power local oscillator (LO) requirements, makes it a promising alternative to heterodyne mixers in the development of large-scale receiver arrays for integrated millimeter-wave and terahertz applications.
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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 | 0.000 | 0.000 |
| 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".