Application of adaptive filtering in mobile communication channel equalization

The effect of adaptive filtering is studied in mobile communication channel equalization. Least-Mean-Square Algorithm (LMS), Normalized Least-Mean-Square Algorithm (NLMS), Sample Matrix Inversion or Least-Squares Method (SMI) and Recursive Least-Squares Algorithm (RLS) are analyzed. It gives the result of simulation experiment based on these algorithms. It compares the merits and shortcomings for these several adaptive algorithms with different channels and different steps. It analyzes the condition of convergence, the rate of convergence, error of steady-state theoretically. The result indicates that Recursive Least-Squares Algorithm has faster rate of convergence than others under high Signal to Noise Ratio, and has the same rate of convergence with Least-Mean-Square-Algorithm under low Signal to Noise Ratio. But RLS can reach less error of steady-state.