| Autor: |
Qingnan Yu, Tony Chan Carusone, Antonio Liscidini |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
IEEE Open Journal of Circuits and Systems, Vol 3, Pp 38-49 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2644-1225 |
| DOI: |
10.1109/OJCAS.2022.3154062 |
| Popis: |
Digital mismatch calibration for quantized analog (QA) signal processing is proposed for the first time. Since the proposed calibration mechanism does not require uniform QA slicer levels, non-uniform quantization can be applied to improve the system performance. We propose two methods utilizing the genetic algorithm and $\mu $ -law to find non-uniform slicer levels offering superior performance compared to uniform levels. Simulations show that for a QA amplifier consisting of 32 slices, the signal-to-noise-and-distortion ratio (SNDR) under a multitone input can be doubled by adjusting only the quantization levels while maintaining the same structure and same power, compared to uniform quantization levels that provide 54 dB of SNDR. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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