WOLA Channelizer Architecture for Lower-Complexity FDMA Processing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Fast-Fourier Transform (FFT)-based filter banks in multiple-channel FDMA receivers are computationally intensive and face difficulties as data rates increase, requiring more efficient channelization methods to manage signal processing in real-time.
Innovation Solution
A channelizer system incorporating a window buffer, weighting logic, time-folding logic, and discrete Fourier Transform (DFT) processes, along with overlap-add (OLA) logic and phase adjustments, to efficiently channelize and filter signals, reducing computational burden and resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If FFT-based filter banks are used for channelization in multiple-channel FDMA receivers, then real-time signal processing capability is achieved, but computational complexity and resource consumption increase significantly
Solution Approach 1:
The patent divides the wideband signal into multiple narrowband sub-bands using filter banks, where each sub-band is processed independently. This segmentation allows parallel processing of multiple channels simultaneously, achieving real-time performance while distributing computational load across multiple simpler filter operations rather than one complex full-band FFT operation.
Solution Approach 2:
The patent applies windowing functions to signal blocks before FFT processing to reduce spectral leakage and improve frequency resolution. This preliminary action prepares the data in advance, reducing the need for iterative adjustments and improving the efficiency of subsequent processing operations.
2Productivity
If simple data rates increase in FFT-based filter banks, then channel capacity improves, but technical difficulties and processing challenges arise
Solution Approach 1:
The patent transforms the time-domain signal into the frequency domain using FFT, adding a frequency dimension to the processing. This allows simultaneous analysis of multiple frequency channels, increasing channel capacity while managing complexity through the structured frequency-domain representation that separates different signal components.
Data Source
AI summary
Systems and methods are provided for channelizing. A first stage can provide a WOLA filter bank that can apply a single multiplier resource to perform window weighting for multiple WOLA filter banks. The first stage can remove mixer-based post FFT adjustment and provide equal functionality with a particular modification of tuning mixers at inputs of second stage FIR paths. The first stage can include a variable decimation, using a particular implementation of variable sample block size.