Pre-Averaged Staggered Convolution Filters for Variable Data Rates
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Solution Overview
Problem
Traditional digital data transmission systems face hardware complexity and inefficiency when accommodating variable data rates, particularly due to the need for increased filter taps, multipliers, and delay elements, and existing solutions like CIC filtering are restrictive and prone to errors.
Innovation Solution
The implementation of a pre-averaged staggered convolution decimating filter, which samples data at a selected rate, pre-averages samples to produce two samples per symbol, and convolves them with decimated FIR aperture impulse response coefficients to produce detected output and zero-crossing transition samples, allowing for adjustable sample rates and reduced hardware complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional linear filtering methods are used to accommodate variable data rates, then data rate flexibility is improved, but hardware complexity grows linearly with the sample rate
Solution Approach 1:
The filter is segmented into multiple stages: a CIC filtering stage followed by a compensating FIR filtering stage. This segmentation allows each stage to handle specific aspects of the filtering requirement, enabling variable data rates without proportionally increasing overall hardware complexity. The CIC stage handles the bulk of the decimation while the FIR stage compensates for its limitations.
Solution Approach 2:
The compensating FIR filter is nested within the overall filtering system after the CIC filter. This nested structure allows the FIR filter to correct the passband errors introduced by the CIC filter without requiring a complete redesign of the entire filtering system, thus managing hardware complexity efficiently.
2Device complexity
If CIC filtering is used to reduce hardware complexity, then hardware requirements are reduced, but pass band control characteristics become restrictive and register widths grow very large
Solution Approach 1:
The compensating FIR filter acts as an intermediary that corrects the passband errors introduced by the CIC filter. It mediates between the simple hardware structure of the CIC filter and the requirement for precise passband control, allowing the CIC filter to handle the heavy lifting while the FIR filter fine-tunes the frequency response.
Solution Approach 2:
The system changes parameters dynamically by adjusting the decimation ratio of the CIC filter and the coefficients of the compensating FIR filter based on the desired data rate and passband requirements. This allows flexible control of passband characteristics without requiring large register widths or complex hardware.
3Speed
If more filter taps, multipliers, and delay elements are added to accommodate higher sample rates, then sample rate capability is improved, but hardware complexity increases by an order of magnitude
Solution Approach 1:
The filtering function is segmented into two distinct parts: the CIC filter handling the primary decimation and the compensating FIR filter handling the frequency response correction. This segmentation allows the system to achieve high sample rates without proportionally increasing the total number of filter taps, multipliers, and delay elements, as each segment is optimized for its specific function.
Data Source
AI summary
Certain embodiments of the invention may include systems and methods for implementing a multirate digital decimating filter for filtering received symbol data. The method may include sampling the received symbol data at a selected sample rate, pre-averaging the sampled received data to provide two samples per symbol; convolving the pre-averaged samples with decimated finite impulse response (FIR) aperture impulse response coefficients to produce detected output samples, convolving the pre-averaged samples with shifted decimated FIR aperture impulse response coefficients to produce zero-crossing transition samples, and adjusting the sample rate based at least in part on averaging the zero-crossing transition samples.