Digital Filter Bank Sampling to Cut Aliasing and Compute Load
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Solution Overview
Problem
Digital filter banks face complexity in implementation due to high signal calculation requirements and are prone to aliasing phenomena due to fixed sample rates, which complicates the reduction of processing bandwidth and reception sensitivity.
Innovation Solution
A signal filtering device and method that generates matrices based on the size of a digital filter bank, performs discrete Fourier transforms, and compensates for phase shifts to adjust sample rates dynamically, preventing aliasing while reducing signal calculation complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a digital filter bank is implemented to divide wideband input signal into narrowband channels, then reception sensitivity is improved and processing bandwidth is reduced, but signal calculation complexity increases
Solution Approach 1:
The filter bank is divided into multiple sub-filter banks, each handling a specific frequency range. Each sub-filter bank processes a portion of the total signal bandwidth, reducing the calculation complexity for each individual filter while maintaining the overall channel division functionality. This segmentation allows parallel processing of multiple frequency bands simultaneously.
Solution Approach 2:
The patent implements variable sample rate adjustment based on the channel number. Different channels use different sample rates optimized for their specific frequency ranges, allowing the system to reduce calculation complexity for higher frequency channels by using lower sample rates, while maintaining reception sensitivity through adaptive rate adjustment.
2Ease of manufacture
If a fixed sample rate is used in the digital filter bank, then implementation is simplified, but aliasing phenomenon occurs
Solution Approach 1:
The system dynamically adjusts the sample rate according to the channel number and frequency characteristics. Lower frequency channels use higher sample rates to maintain signal fidelity, while higher frequency channels use lower sample rates to reduce calculation complexity. This dynamic adjustment prevents aliasing by ensuring each channel operates at an appropriate sample rate for its frequency range.
Solution Approach 2:
The patent changes the sample rate parameter based on channel characteristics. By varying the sample rate parameter across different channels rather than using a fixed value, the system eliminates aliasing phenomena while maintaining implementation feasibility through systematic parameter adjustment rules.
3Reliability
If the processing bandwidth is reduced to improve reception sensitivity, then signal-to-noise ratio improves, but aliasing phenomena occur due to insufficient sampling
Solution Approach 1:
The wideband signal is segmented into multiple narrowband channels, each processed with an optimized sample rate. This segmentation allows each channel to achieve sufficient sampling for its specific bandwidth without requiring excessive sample rates across the entire wideband signal, thereby preventing aliasing while maintaining good signal-to-noise ratio in each channel.
Solution Approach 2:
The sample rate is dynamically adjusted for each channel based on its frequency characteristics and bandwidth requirements. This dynamic adjustment ensures that each narrowed bandwidth channel is sampled at an appropriate rate to prevent aliasing, while the overall system maintains high reception sensitivity through optimized processing of each frequency band.
Data Source
AI summary
This application relates to a signal filtering device. The device includes a memory and a processor. The processor may generate one or more matrices based on a size of a digital filter bank that generates an output signal by dividing an input signal into a plurality of channels and store in the memory each of the generated one or more matrices to which a plurality of digital filter bank coefficients or a plurality of input signals are assigned. The processor may also partially calculate the stored plurality of digital filter bank coefficients and the plurality of signals based on a number of at least some of the plurality of channels, and calculate the calculated digital filter bank coefficients and signals. The processor may further perform a discrete Fourier transform (DFT) on the calculated signal and compensate for a phase of the discrete Fourier transformed signal according to a preset reference.