一种并行双模式盲均衡算法的研究与实现

本文提出了一种将SMMA算法与DD算法并行运行的变步长双模式盲均衡算法。该算法在保持原来两种算法高性能的基础上，改进传统的DD算法，将两种算法采用并行结构运行，同时加入误差控制函数，控制SMMA算法占比，降低稳态误差；并且引入变步长方法，加快算法的收敛速度。经过理论分析与仿真实验表明，该算法相对于传统方法，ISI降低到-29.8 dB，收敛速度提高，在630个符号左右算法完成收敛。在完成仿真实验后，进行了实测信号的解调均衡，其EVM降低到1.69%。

Research and implementation of a parallel dual-mode blind equalization algorithm

This paper proposes a variable step-size dual-mode blind equalization algorithm that runs the SMMA algorithm and the DD algorithm in parallel. On the basis of maintaining the high performance of the original two algorithms, this algorithm improves the traditional DD algorithm, runs the two algorithms in a parallel structure, and at the same time adds an error control function to control the proportion of the SMMA algorithm, reduce the steady-state error. Theoretical analysis and simulation experiments show that compared with the traditional method, ISI is reduced to -29.8 dB, and the convergence speed is improved, and the algorithm completes the convergence at about 630 symbols. After the completion of the simulation experiment, demodulation equalization of the measured signals was conducted, and the EVM was reduced to 1.69%.