ADC Errors and Signal-to-Quantization-Noise Ratio
## Quantization vs. Sampling: "Opposite" Operations
ADC Errors and Signal-to-Quantization-Noise Ratio
Quantization vs. Sampling: “Opposite” Operations
| Aspect | Sampling | Quantization |
|---|---|---|
| Axis discretized | Time ($x$-axis) | Amplitude ($y$-axis) |
| Continuous → | Discrete-time | Discrete-valued |
| Information loss | Aliasing (if undersampled) | Quantization noise |
| Control parameter | Sampling frequency $F_s$ | Number of bits $B$ |
| Reversibility | Perfect if Nyquist met | Never perfectly reversible |
Key insight: Sampling can be lossless (Nyquist); quantization is always lossy. The lost information becomes quantization noise.
ADC Stage Errors
An Analog-to-Digital Converter introduces errors at multiple stages:
1
2
3
4
Analog Input → Sample & Hold → Quantizer → Encoder → Digital Output
│ │ │
Aperture Quantization Encoding
Jitter Noise Errors
| Error Source | Description | Mitigation |
|---|---|---|
| Quantization error | Fundamental, unavoidable | Increase bits $B$ |
| Aperture jitter | Uncertainty in sampling instant | Better clock, lower jitter |
| Integral non-linearity (INL) | Deviation from ideal transfer curve | Calibration, better ADC |
| Differential non-linearity (DNL) | Uneven step sizes | Laser trimming, calibration |
| Offset/Gain error | Systematic shift/scale error | Calibration |
The quantization stage is the only one that fundamentally cannot be eliminated—only reduced by using more bits.
Signal-to-Quantization-Noise Ratio (SQNR)
For a full-scale sinusoidal input with $B$ bits:
\[\text{SQNR} \approx 6.02B + 1.76 \text{ dB}\]| Bits | SQNR (dB) | Typical Application |
|---|---|---|
| 8 | 49.9 | Basic audio, sensors |
| 12 | 74.0 | Instrumentation, audio |
| 16 | 98.1 | CD audio, precision DAQ |
| 24 | 146.2 | Professional audio, scientific |
Non-Uniform Quantization (Advanced)
For signals with non-uniform amplitude distributions (e.g., speech—mostly small amplitudes, occasional large peaks), non-uniform quantization allocates more levels where the signal spends more time.
- $\mu$-law (North America/Japan): $\mu = 255$
- A-law (Europe): $A = 87.6$
These provide ~24 dB improvement for speech at 8 bits vs. uniform quantization.
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