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针对常数模盲均衡算法(CMA)均衡高阶正交振幅调制信号(QAM)存在收敛速度慢、稳态误差大的缺点,提出了基于量子粒子群优化的正交小波加权多模盲均衡算法(QPSO-WTWMMA).该算法根据高阶QAM信号星座图分布特点,将量子粒子群优化算法(QPSO)和正交小波变换融入于加权多模盲均衡算法(WMMA)中.因而,利用QPSO对均衡器权向量进行了优化,利用正交小波变换降低了输入信号的自相关性,利用WMMA选择了合适的误差模型匹配QAM星座图.理论分析及水声信道仿真结果表明,QPSO-WTWMMA算法可以获得更快的收敛速度和更低的稳态误差,在水声通信中具有重要的参考价值.
In order to solve the problem that the constant modulus blind equalization algorithm (CMA) has the disadvantages of slow convergence rate and large steady-state error, an orthogonal wavelet weighted multi-mode blind equalization algorithm based on quantum particle swarm optimization (QPSO-WTWMMA) .According to the distribution characteristics of high-order QAM constellation, this algorithm incorporates Quantum-behaved Particle Swarm Optimization (QPSO) and Orthogonal Wavelet Transform into weighted multi-mode blind equalization algorithm (WMMA) The equalizer weight vector is optimized, and the autocorrelation of the input signal is reduced by orthogonal wavelet transform, and the suitable error model is selected to match the QAM constellation using WMMA.Theoretical analysis and acoustic channel simulation results show that the QPSO-WTWMMA algorithm can Get faster convergence rate and lower steady-state error, has important reference value in underwater acoustic communication.