MATLAB Implementation of an Adaptive Blind Signal Equalizer in Complex Domain

This MATLAB routine demonstrates the implementation of an adaptive blind signal equalizer operating in the complex domain. Adaptive blind equalization is a crucial signal processing technique that enables signal recovery and interference cancellation when dealing with complex-valued received signals. The implementation utilizes stochastic gradient-based algorithms, such as the Constant Modulus Algorithm (CMA) or Godard algorithm, which operate without requiring training sequences. Key MATLAB functions employed include complex number handling, adaptive filter structures using FIR filters, and iterative weight updates through gradient descent optimization. The code implements constellation point recovery by minimizing dispersion cost functions that measure signal modulus deviations from ideal constant modulus properties. Through this routine, you will learn practical implementation techniques for blind equalization algorithms, including complex signal processing methods, adaptive filter design considerations, and performance evaluation metrics such as convergence rate analysis and inter-symbol interference reduction measurements.