A Quad-Channel 11-bit 1-GS/s 40-mW Collaborative ADC Enabling Digital Beamforming for 5G Wireless
Bibliographic record
Abstract
A 4 × 11 bit 1-GS/s 40-mW collaborative analog-to-digital converter (ADC) is presented in a 65-nm CMOS for a four-channel multiple-input and multiple-output (MIMO) receiver. This work extends the maximal-ratio-combining (MRC) approach to define the ADC resolution in a multichannel environment to maximize the signal-to-noise ratio (SNR) in a power-constrained application. The ADC takes the advantage of the channel diversity by distributing the resolution according to the channel SNR. In addition, it utilizes the correlated information between channels to perform energy-efficient digitization of received signals. The collaborative ADC is designed with eight successive-approximation-register (SAR) ADC units each having a 6-bit of resolution and a 2-bit flash to monitor SNR. With the help of a coarse 2-bit flash, the ADC can detect change in channel SNR and accordingly reconfigure the four ADCs with a variable resolution from 6 to 11 bits with less than 1-ns mode switching time. This collaborative ADC performance is compared with four channel ADCs with uniform 11 and 9 bits of resolution. It reduces area and power by half and 41%, respectively, with only 10% degradation of overall signal-to-noise and distortion ratio (SNDR).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".