Uniform Sample Reconstruction for Time-Skewed TI ADCs
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Solution Overview
Problem
Conventional methods for reconstructing uniform digital signal samples from nonuniform samples, particularly in time-interleaved analog-to-digital converters (ADCs), face challenges such as high implementation complexity, increased power consumption, and lower convergence rates due to time-skew errors caused by component aging and temperature variations, especially when dealing with multiple channels and varying time-skew errors.
Innovation Solution
The use of variable digital filters (VDFs) and iterative methods like Richardson, Jacobi, and Gauss-Seidel iterations, implemented with a Farrow structure, to approximate ideal fractional delay operations, reducing the need for general-purpose multipliers and minimizing computational complexity, while allowing for real-time adjustments to handle timing mismatches.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional filter bank structures are used for reconstruction, then reconstruction capability is achieved, but implementation complexity and power consumption increase
Solution Approach 1:
The filter bank structure is segmented into multiple polyphase components (E1 through EM), where each component processes a specific subset of the input signal. This segmentation allows parallel processing and reduces the computational burden on each individual filter, thereby lowering overall implementation complexity while maintaining reconstruction accuracy.
Solution Approach 2:
The synthesis filter bank is designed with universal polyphase components that can handle multiple reconstruction scenarios. The same structural framework processes both uniform and nonuniform sampled signals by adjusting the timing parameters, eliminating the need for separate dedicated structures for different signal types and reducing overall system complexity.
2Measurement precision
If time varying FIR filters are used to address timing mismatch, then timing error correction is improved, but power consumption increases at high data rates
Solution Approach 1:
The synthesis filter bank employs periodic polyphase components that are reused across different time periods and signal cycles. By structuring the filters with periodic characteristics matching the sampling pattern, the system achieves timing mismatch correction through regular, efficient operations rather than continuous complex computations, reducing power consumption at high data rates.
3Adaptability or versatility
If sophisticated multivariate polynomial filters are used, then tunability is improved, but design difficulty and implementation complexity increase
Solution Approach 1:
The filter bank implements dynamic polyphase components that can adapt their characteristics based on input signal properties and timing requirements. The structure allows real-time adjustment of filter parameters through simple coefficient modifications rather than complex redesign, maintaining tunability while reducing design difficulty through a standardized dynamic framework.
Data Source
AI summary
Briefly, embodiments of methods or structures for reconstruction of uniform digital signal sample values from nonuniform digital signal sample values are disclosed.