Adaptive Channel Equalization Using LMS Algorithm
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Resource Overview
Implementation of LMS-based adaptive channel equalization with QPSK training signals, featuring constellation diagram visualization for intuitive result analysis
Detailed Documentation
Based on research into LMS-based adaptive channel equalization, we employ QPSK signals as training sequences. When observing the constellation diagram results, we can obtain intuitive information about the equalization performance. The implementation typically involves initializing LMS filter coefficients, calculating the error signal between the desired and actual output, and iteratively updating weights using the LMS adaptation algorithm. Key functions include generating QPSK modulation, implementing the LMS update rule (w(n+1) = w(n) + μ*e(n)*x(n)), and plotting constellation diagrams to visualize the equalizer's ability to compensate for channel distortion.
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