Multi-Mode ADC Noise Shaping for Wideband High-Resolution Sampling
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Solution Overview
Problem
Conventional multi-mode analog-to-digital converters (ADCs) face limitations in achieving high-resolution, wide-bandwidth signal conversion due to practical implementation impairments such as sampling jitter, thermal noise, and rounding errors, which restrict their performance in multi-mode applications.
Innovation Solution
The use of Multi-Channel Bandpass Oversampling (MBO) technique, which involves decomposing input signals into distinct frequency subbands, independently processing each subband, and combining them to preserve bandwidth, utilizing continuous-time quantization-noise-shaping circuits, sampling/quantization circuits, and digital bandpass filters to enhance resolution and reduce noise sensitivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional ADC approaches are used to achieve high-resolution conversion, then conversion precision is improved, but input bandwidth is limited to a few gigahertz or less
Solution Approach 1:
The input signal is divided into multiple frequency subbands, each processed by a separate processing branch. This segmentation allows the system to achieve high resolution for narrowband signals while maintaining wide overall bandwidth by parallel processing of multiple subbands.
Solution Approach 2:
The converter dynamically reconfigures its operation mode based on input signal characteristics. It can switch between high-resolution low-rate conversion mode and high-rate moderate-resolution conversion mode, adapting to different application requirements in real-time.
2Speed
If the sample rate is increased to expand instantaneous bandwidth, then input bandwidth is improved, but quantization noise increases and resolution deteriorates
Solution Approach 1:
A feedback loop continuously monitors the quantization noise characteristics and dynamically adjusts the noise shaping filter parameters. This feedback mechanism suppresses quantization noise in the signal band while maintaining high sample rates, thereby preserving resolution despite increased bandwidth.
Solution Approach 2:
The system changes the noise shaping filter parameters dynamically based on the operating mode and input signal characteristics. By adjusting these parameters, the system optimizes the trade-off between bandwidth and resolution for different conversion scenarios.
3Measurement precision
If conventional ADCs are designed for narrowband high-precision conversion, then resolution is improved, but adaptability to wideband signals is reduced
Solution Approach 1:
The converter is designed with multiple processing branches and reconfigurable noise shaping filters that enable it to perform multiple functions. It can handle both narrowband high-precision conversion and wideband moderate-resolution conversion, as well as interpolate between these extremes, making it universally applicable to various conversion scenarios.
Data Source
AI summary
Provided are, among other things, systems, methods and techniques for converting a continuous-time, continuously variable signal into a sampled and quantized signal. According to one implementation, an apparatus includes multiple processing branches, each including: a continuous-time quantization-noise-shaping circuit, a sampling/quantization circuit, and a digital bandpass filter. A combining circuit then combines signals at the processing branch outputs into a final output signal. The continuous-time quantization-noise-shaping circuits include adjustable circuit components for changing their quantization-noise frequency-response minimum, and the digital bandpass filters include adjustable parameters for changing their frequency passbands.