Time-domain front-end for short time windowing UWB WLAN transform-domain receiver
Bibliographic record
Abstract
This paper addresses the selectivity problem, for the ultra-wide band (UWB), transform-domain receiver loss of orthogonality. A novel selective time-domain direct-sequence front-end for transform-domain ultra-wideband (UWB) wireless local area network (WLAN) receiver is proposed. The architecture comprises a multi-block, linear, dynamic feedback low-noise amplifier (LNA), quadrature mixer, and baseband filter. The dynamic feedback with inductive output load reduces the LNA to a simple second-order filter, with zero at the origin, while improving the conversion gain (CG) and noise figure (NF). Thus, the CG is further maximized when limiting the two poles within the 5-6 GHz frequency band. The mixer, based on a merged quadrature topology, employs single-peak notch network, with benefits to the NF and IIP3 of CG at 5.6 GHz. The front-end dissipates a 19.6 mW from 1.8 V supply voltage and achieves at 5.6 GHz 34.8 dB conversion gain, 6.42 dB NF, and 1-dB gain desensitization with -8 dBm interferer power at 7 GHz. Other simulation results are -2.35 dBm minimum IIIP3, and -35 dBc rejection at the UWB group #3.
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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) | 0.002 | 0.001 |
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".