A multiband /spl Delta//spl Sigma/ fractional-N frequency synthesizer for a MIMO WLAN transceiver RFIC
Bibliographic record
Abstract
This work presents a shared fractional-N synthesizer used by two dual-band 802.11 radios integrated on a single chip for 2/spl times/2 multiple-input multiple-output (MIMO) applications. Additional 2/spl times/2 MIMO chips can be used in a system by phase synchronizing the signal paths through a bidirectional LO porting scheme developed for this application. This synthesizer was fully integrated with the exception of an off-chip loop filter. The synthesizer is a /spl Delta//spl Sigma/-based fractional-N frequency synthesizer with three on-chip LC tuned VCOs to cover the entire frequency bands specified in the IEEE 802.11a/b/g and Japanese WLAN standards. The radio uses a variable IF frequency so that both the RF LO and IF LO can be derived from a single synthesizer saving chip area and power. The synthesizer includes a programmable second/third-order /spl Delta//spl Sigma/ noise shaper, a phase frequency detector, a differential charge pump, and a 6-bit multimodulus divider (MMD). The nominal jitter from 100 Hz to 10 MHz is 0.63-0.86/spl deg/ rms in the 5-GHz band and 0.35-0.43/spl deg/ rms in the 2.4-GHz band. The maximum frequency deviation of the synthesizer when enabling the transmitter is less than 150 kHz and the frequency error settles to 2 kHz in less than 12 /spl mu/s. For MIMO applications requiring more than two full paths, a single synthesizer on one die can be used to generate the LOs for all other radios integrated in different dies.
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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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".