Iterative Digital Filter Synthesis for Inter-Symbol Interference Reduction
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Solution Overview
Problem
Existing methods for synthesizing digital filters for narrow band wireless transmission with single-carrier modulation face challenges in achieving good interference reduction and crest factor performance while maintaining a constrained length, especially when processor capacity is limited, and existing solutions either apply only to multi-carrier modulations or require specific windowing functions.
Innovation Solution
An iterative method for synthesizing digital filters that compensates for inter-symbol interference by convolving the transmission filter with the reception filter, allowing adaptation of filter parameters to constraints, and using a weighting window to control convergence speed, with iterations stopping when inter-symbol interference is below a threshold.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If root raised cosine filters are used with a large number of coefficients, then interference between symbols is eliminated and spectral characteristics are improved, but filter length increases and processing complexity increases
Solution Approach 1:
The filter synthesis is divided into iterative segments where an equalizer filter is progressively applied and refined over multiple iterations. Each iteration segment improves the interference cancellation capability while maintaining control over the final filter length through the iterative refinement process.
Solution Approach 2:
The filter coefficients are made dynamic through iterative adjustment. The equalizer filter is repeatedly applied and refined, allowing the filter to adaptively optimize its coefficients to minimize inter-symbol interference while converging to a solution with controlled length suitable for processing constraints.
2Manufacturing precision
If root raised cosine filters are used with a large number of coefficients, then spectral characteristics are improved, but processing complexity increases proportionally to filter length
Solution Approach 1:
The complex filter design process is segmented into iterative steps where a base filter is repeatedly refined by applying an equalizer filter. This segmentation allows achieving high spectral precision through multiple passes of simpler operations rather than requiring a single complex high-order filter.
Solution Approach 2:
The iterative method employs feedback by repeatedly applying the equalizer filter to the transmission filter and evaluating the result. The process uses the outcome of each iteration to guide the next refinement, creating a feedback loop that converges to an optimal solution with controlled complexity.
3Device complexity
If filter length is reduced to satisfy processor capacity constraints, then processing complexity decreases, but interference between symbols increases
Solution Approach 1:
The equalizer filter is applied in advance through multiple iterative passes before the final filter is deployed. This preliminary iterative refinement prepares the filter coefficients to maximize interference cancellation capability within the constrained length, ensuring optimal performance before actual transmission.
Solution Approach 2:
The method changes the parameters of the filter by iteratively adjusting coefficients through equalizer application. By modifying the filter parameters repeatedly in controlled iterations, the system achieves better interference rejection than a single-pass design would allow, within the constraints of reduced filter length.
4Manufacturing precision
If weighting windows are applied to truncated filters to improve performance, then spectral characteristics are improved, but interference between symbols is generated
Solution Approach 1:
Instead of applying windowing functions that create interference, the method inverts the approach by using iterative equalizer filtering to actively cancel interference. Rather than passively shaping the filter with windows that introduce artifacts, the active iterative refinement process removes interference while maintaining spectral properties.
Solution Approach 2:
The method converts the potential harm of truncation into a benefit by using the truncated filter as a starting point for iterative equalizer application. The initial truncation that would normally create interference is transformed into a manageable base that can be refined iteratively to eliminate the interference while preserving the compact structure.
Data Source
AI summary
An iterative method for synthesizing digital filters comprising the following steps: • The generation of a transmit filter (101) for application to a signal to be transmitted, • The generation of a receive filter (102) for application to a received signal, said method being characterized in that it comprises the following steps performed iteratively: • The convolution (107) of the transmit filter and the receive filter to generate a transmission filter, • The determination (108) of a criterion representative of the level of inter-symbol interference on said transmission filter and whether the level of inter-symbol interference is greater than a given level, • The calculation of an equalization filter for the inter-symbol interference (110), • The replacement of the transmit filter by the convolved transmit filter (105) with the equalization filter or the replacement of the receive filter by the convolved receive filter (106) with the equalization filter.