An 8-bit 2-GSample/s folding-interpolating analog-to-digital converter for LMDS applications
Bibliographic record
Abstract
This thesis deals with the design and implementation of a high speed high resolution analog-to-digital converter (ADC) which is an essential component in a direct IF sampling receiver for the base station of LMDS wireless communication systems. The ADC features an 8-bit resolution, a 2-GSample/s sampling rate and is implemented in a 0.5 mum BiCMOS SiGe process with a unity gain cut off frequency of 47 GHz. A folding-interpolating architecture is used in the converter to provide the GHz sampling rate, wide bandwidth and high resolution as well as reduce the power dissipation and chip area of the circuit. The 8-bit, 2-GSample/s A/D converter consists of a track-and-hold amplifier, a reference ladder, four folding amplifiers, a comparator array, a digital encoder including an XOR array and a 31-to-5 ROM and a coarse quantizer. The chip area is 3.5 x 3.5 mm2 including pads and buffer circuits. The ADC exhibits a maximum signal-to-noise and distortion ratio (SNDR) of 47 dB corresponds to an effective number of bits (SNOB) of 7.45 bits and an effective resolution bandwidth (ERBW) of 700 MHz. The circuit demonstrates a maximum differential nonlinearity (DNL) and integral nonlinearity (INL) of 0.5 and 1 LSB, respectively. The chip consumes 3.5 W from a single -3.3 V power supply. The ADC exceeds the LMDS architecture specifications and is the highest performance GSample/s ADC reported to date. Local multi-point distribution system (LMDS) is a terrestrial cellular broadband communication system operating in the 28 GHz band. LMDS provides two-way wireless transmission for data, video and voice and allows for interactive services.
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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) | 0.008 | 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".