Digital Interpolation Filter With Configurable Newton Structures
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Solution Overview
Problem
Current interpolator filters face challenges in efficiently adapting their frequency and time response due to high computational complexity and the need for reconfiguration when switching between different signal standards, limiting their applicability in multi-mode receivers.
Innovation Solution
A digital interpolator filter with a configurable frequency and time response is achieved through a combination of Newton structures and a linear combination of transfer functions, allowing for simple hardware implementation and adaptable response configuration using a minimal number of parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a Farrow structure is used to implement polynomial interpolation with adaptable frequency response, then the filter can be reconfigured for different signal standards, but the computational complexity becomes non-negligible and hardware implementation is complex
Solution Approach 1:
The Farrow structure is segmented into multiple Newton structures, each implementing a specific polynomial interpolation. By dividing the overall interpolation function into discrete polynomial components that can be independently implemented using Newton structures, the system achieves reconfigurability while maintaining manageable computational complexity for each segment.
Solution Approach 2:
Multiple Newton structures are designed to perform different polynomial interpolations (Lagrange-type, Spline-type, Hermite-type) using a common computational framework. This universal approach allows the same hardware architecture to be reconfigured for different signal standards and interpolation types, reducing overall system complexity while maintaining adaptability.
2Device complexity
If the filter structure is fixed with a chosen interpolation order and polynomial type, then hardware implementation is simplified, but the frequency response cannot be adapted to different signal standards
Solution Approach 1:
The filter structure incorporates dynamic reconfiguration capability through multiple Newton structures that can be selectively activated. The system transitions from a static fixed-structure filter to a dynamic multi-structure system where the appropriate Newton structure is selected based on the required signal standard, enabling both hardware simplicity and frequency response adaptability.
Solution Approach 2:
The system changes operational parameters by selecting different polynomial types (Lagrange, Spline, Hermite) and different interpolation orders through the activation of specific Newton structures. This parameter-based reconfiguration allows the same hardware to adapt its frequency response characteristics without physical reconfiguration, maintaining implementation simplicity while achieving versatility.
3Adaptability or versatility
If completely reconfiguring the interpolating filter response is done to adapt to new reception signal standards, then the filter can handle different standards, but computational complexity increases and requires computing/storing complete sets of filter parameters for each configuration
Solution Approach 1:
The Newton structures are pre-configured with fixed polynomial interpolation algorithms (Lagrange, Spline, Hermite) and their corresponding parameters are predetermined. When adapting to new signal standards, the system simply selects the appropriate pre-configured Newton structure rather than computing new parameters, eliminating the need for real-time parameter computation and reducing storage requirements.
Solution Approach 2:
Instead of completely reconfiguring the filter for each signal standard, the system uses copies of predefined Newton structures that implement different polynomial interpolations. Each Newton structure is a ready-made computational template that can be activated without computation, allowing rapid adaptation to different standards while minimizing parameter storage overhead.
Data Source
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AI summary
The invention concerns a digital interpolation filter delivering a series of output samples approximating a signal x(t) at sampling instants of the form (n + d)T s based on a series of input samples of the signal x(t) taken at sampling instants of the form nT s . Such a filter implements a transfer function in the Z-transform domain, H c d (Z -1 ), expressed as a linear combination between: a first transfer function H 1 d (Z -1 ) representing a Lagrange polynomial interpolation of the input samples implemented according to a Newton structure (100); and a second transfer function H 2 d (Z -1 ) representing another polynomial interpolation of the input samples implemented according to another structure comprising at least the Newton structure; the linear combination being a function of at least one real combination parameter c.