DEM DAC with RTZ Switching for Lower Code-Dependent Distortion
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Solution Overview
Problem
Conventional digital to analog converters suffer from glitches and current mismatch issues due to correlated switching transients, which degrade the spurious free dynamic range (SFDR) and introduce distortion tones.
Innovation Solution
A digital to analog conversion method that implements a randomization function using dynamic element matching (DEM) by generating a random rotation number for each binary-weighted input code, rotating the codes, and inserting a pre-determined return-to-zero (RTZ) code to randomize current source selection, thereby suppressing transition nonlinearity and mitigating mismatch- and transient-related distortion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If conventional digital return-to-zero technique is used with fixed current groups, then the DAC structure is simple and easy to implement, but switching transients are correlated with input codes causing distortion tones and degrading SFDR
Solution Approach 1:
The patent applies dynamics by making the current group assignment variable rather than fixed. The binary-weighted input code dynamically determines which current sources are activated in each phase, breaking the fixed correlation between input codes and switching transients. This dynamic assignment improves SFDR by randomizing the switching behavior while maintaining implementation feasibility.
Solution Approach 2:
The patent changes the parameter of current source activation by inverting the binary-weighted input code to determine current group selection. Instead of directly activating current sources based on the input code, the inverted code determines which current sources remain inactive during signal phase and which are activated during RTZ phase. This parameter transformation disrupts the harmful correlation between input codes and switching transients.
2Stability of the object's composition
If mid-code is used for return-to-zero phase, then the transition nonlinearity is reduced, but the same unit current source is always switched for the same input code creating correlated glitches
Solution Approach 1:
The patent applies inversion by reversing the conventional approach: instead of using mid-code to determine which current sources switch during RTZ phase, the inverted binary-weighted input code determines which current sources remain inactive. This inversion strategy ensures that the same input code produces different switching patterns, eliminating correlated glitches while maintaining transition stability.
3Ease of operation
If binary-weighted input codes directly control unit current sources, then the conversion is straightforward, but current mismatch and switching transient issues degrade converter accuracy
Solution Approach 1:
The patent transforms the control parameter by inverting the binary-weighted input code before using it to control current sources. This parameter change modifies the relationship between input codes and current source activation, breaking the direct correlation that causes mismatch and transient issues. The inverted code provides the same control functionality while eliminating the harmful effects on converter accuracy.
Data Source
AI summary
A digital to analog converting method insensitive to code-dependent distortions is implemented by a digital to analog converter (DAC) having a plurality of unit current sources. A plurality of binary-weighted input codes are received by the DAC and rotated to generate dynamic element matched (DEM) encoded signals. Between the adjacent DEM encoded signals is a purposely added pre-determined return-to-zero (RTZ) code. When the DAC generates analog outputs according to the alternately received DEM encoded signals and the RTZ codes, a zero-voltage phase during the level transition of the analog outputs is obtained by the RTZ codes. With the DEM encoded signals and the RTZ codes, each level transition is independent. Furthermore, code-dependent problems such as mismatch- and transient-related distortion are mitigated by the DEM encoded signals.