A Low-Power Wideband Receiver Front-End for NB-IoT Applications
Bibliographic record
Abstract
A low-power wideband receiver front-end is proposed for the narrow-band internet of things (NB-IoT) wireless standard to cover frequency bands from 0.6GHz to 1.4GHz. The front-end receiver integrates a programmable gain quadrature RF-to-baseband (BB) current-reuse receiver (CRR) architecture using conventional double-balanced passive-mixer with 25% duty-cycle local oscillator (LO) followed by a passive polyphase filter (PPF), high pass filter (HPF), programmable gain gm-C filter and RC-low pass filter (LPF). Low-power consumption is achieved by employing RF-to-BB CRR that shares a single supply with a wideband transconductor and a transimpedance amplifier (TIA). Moreover, power consumption is reduced by employing a single path PPF and gm-C filter to attenuate the blocker frequency at 7.5MHz above the intermediate frequency (IF). The proposed architecture is post-layout simulated in TSMC 130-nm CMOS technology. It achieves a voltage gain of 59.4dB, a noise figure (NF) of 4.9dB and a out-of-band IIP3 of -34.2dBm at 900MHz while consuming 1.8mW from a 1.2V supply at the maximum gain setting. In addition, the input matching covers several NB-IoT frequency-bands.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".