A Frequency-Agile RF Frontend Architecture for Multi-Band TDD Applications
Why this work is in the frame
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Bibliographic record
Abstract
Emerging wireless standards specify dozens of bands spanning several octaves, which need to be supported in form-factor and energy constrained mobile devices targeting ubiquitous connectivity. However, in current multi-band radio implementations, significant redundancy is still the norm in the RF frontend. This work introduces an improved architecture for multi-band, time-division duplexed (TDD) radios, which replaces multiple narrowband frontend components with a frequency-agile solution, tunable over a wide frequency range. A highly digital architecture is adopted, leading to a fully integrated solution wherein both efficiency and achievable frequency range benefit from CMOS scaling. A prototype is integrated in 45 nm SOI CMOS. Peak PA output power is 27.7 ±0.5 dBm from 1.3 to 3.3 GHz, with up to 30% total efficiency at 2 V. For TDD LTE applications, better than -30 dBc ACLR and -30 dB EVM is measured with 64 QAM, 20 MHz signals from 1.44 to 3.41 GHz, with up to 17.2% average efficiency and 23.4 dBm average power. The LNA achieves AV ≥ 14 dB, NF = 4.4 ±1.6 dB and IIP 3 ≥ -7 dBm from 1.3 to 3.3 GHz while drawing just 6 mA from 1 V. The demonstrated frequency range covers a total of 11 TDD bands .
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it