Frequency-Domain Equalizer Reducing Matrix Inversion Overhead
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Solution Overview
Problem
Existing Linear Minimum Mean Squared Error (LMMSE) equalizers in communication systems face significant computational and cost overhead due to the need for inverting large matrices, particularly in mobile environments with rapid channel state changes, which makes them expensive to implement in mobile handsets.
Innovation Solution
The method involves calculating optimal filter weights in the frequency domain without explicit matrix inversion, using a Fast Fourier Transform (FFT) processor and Inverse FFT (IFFT) to replace convolution with multiplication, reducing the need for matrix inversion and minimizing computational complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If LMMSE equalization is used to achieve resilience to multipath distortion, then signal equalization performance is improved, but computational complexity and cost overhead increase due to the need for inverting large matrices
Solution Approach 1:
The patent replaces the traditional time-domain LMMSE equalization approach (which requires explicit matrix inversion) with a frequency-domain implementation using FFT-based convolution. This substitution transforms the computational mechanism from direct matrix operations to frequency-domain multiplication, significantly reducing computational complexity while maintaining equalization performance
Solution Approach 2:
The patent changes the domain parameter from time-domain to frequency-domain processing. By transforming the equalization operation into the frequency domain using FFT, the computational characteristics change fundamentally - convolution becomes multiplication and matrix inversion is avoided, thereby resolving the contradiction between performance and complexity
2Reliability
If traditional time-domain LMMSE equalization is implemented, then signal equalization is achieved, but the number of computational operations is high making it expensive for mobile handsets
Solution Approach 1:
The patent substitutes the computationally intensive time-domain matrix inversion mechanism with a frequency-domain approach using FFT-based convolution. This replacement dramatically reduces the number of computational operations required, making the equalization algorithm feasible for implementation in cost-sensitive mobile handset devices
3Measurement precision
If matrix inversion is performed in time-domain LMMSE equalization, then optimal filter weights are obtained, but computational overhead increases significantly
Solution Approach 1:
The patent replaces the matrix inversion operation with frequency-domain convolution implemented through FFT-based multiplication. This substitution maintains the accuracy of filter weight calculation while dramatically improving computational efficiency, as convolution in the frequency domain requires far fewer operations than explicit matrix inversion in the time domain
Data Source
AI summary
A system and apparatus are disclosed for a method and apparatus for equalizing signals. An apparatus that incorporates teachings of the present disclosure may include, for example, an equalizer (100) having a channel estimation calculator (102) for calculating a time domain channel estimation from a baseband signal, an FFT processor (104) for translating the time domain channel estimation to a frequency domain channel estimation, a tap weight calculator (106) for calculating a frequency domain tap weight according to the frequency domain channel estimation, an inverse FFT processor (108) for translating the frequency domain tap weight calculation to a time domain tap weight calculation, and a filter (110) for equalizing the baseband signal according to the time domain tap weight calculation.