A Variable Step Size MSEI-DDLMS Double Mode Blind Equalization Algorithm
Shuai Wang, Qian Wang, Xihai Xie · 2021 4th International Conference on Artificial Intelligence and Pattern Recognition · 2021
The quality of communication is seriously affected by ICI in communication. Blind equalization can solve this problem well. In this paper, the fixed step length modified super-exponential iterative blind equalization (MSEI) algorithm is introduced. The convergence speed and steady-state error of the fixed step length MSEI-DDLMS double mode blind equalization algorithm is restricted, which leads to the poor convergence effect of the algorithm and some probability of failure to converge. To solve this problem, a variable step-size MSEI-DDLMS algorithm is proposed. In the initial stage of the algorithm, the step size of the MSEI algorithm is adjusted automatically according to the change of the error to ensure rapid convergence in the early stage. After stabilization, it is switched to DDLMS algorithm with smaller residual mean square error, and the step size of DDLMS algorithm is further adjusted to reduce the steady-state error. The algorithm analysis and simulation results show that the improved algorithm has faster convergence speed and higher convergence efficiency.