A Wideband Low-Power Current-Reuse RF-to-BB Receiver Using a Clock Strategy Technique
Bibliographic record
Abstract
A wideband and low-power RF-to-baseband (BB) current-reuse receiver (CRR) front-end that employs a clock strategy is proposed to support software-defined radios (SDRs). It includes a capacitively cross-coupled common-gate low noise transconductance amplifier (LNTA) to amplify and convert the RF voltage to a current, a passive mixer to down-convert the RF current at 4 × the local-oscillator (LO) frequency to the intermediate frequency (IF) current using a clock strategy, an active-inductor (AI) technique to improve the noise-figure (NF) performance, and a transimpedance amplifier (TIA) to convert the IF current to a voltage at the output. To achieve low power consumption the receiver features: current-reuse between the LNTA and the BB circuits; current-mode harmonic recombination at the output of the passive mixer; and a clock strategy to reduce the dynamic power consumption of the clock generation for the dividers and the LO buffers. The proposed receiver is implemented in 22-nm CMOS technology and occupies an active area of 0.13mm2. In the nominal condition, at an IF of 10MHz and an RF of 2.4GHz, it achieves a voltage gain of 36dB, a double-sideband (DSB) noise figure (NF) of 5.2dB, S11of less than −10dB and an IIP3 of −18.5dBm while consuming 2.44mA from a 1.2V supply voltage.
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".