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Variable Step-Size Modified Constant Modulus Blind Equalization Algorithm

机译:变步长修正恒模盲均衡算法

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This paper presents a new blind equalization algorithm based on MCMA to attain fast convergence speed and low steady-state error. The channel equalization without resorting to training sequence is called blind equalization. The CMA (Constant Modulus Algorithm) and MCMA (Modified Constant Modulus Algorithm) are two widely referenced algorithms for blind equalization of a QAM system. These algorithms exhibit very slow convergence rates and large steady-state mean square error when compared to algorithms employed in conventional equalization schemes. To obtain better results, we used varying step-size in MCMA, based on estimate of error at the output of equalizer. Simulation results show that the proposed algorithm has a better convergence rates and lower steady state error in comparison to CMA and MCMA algorithms.
机译:提出了一种新的基于MCMA的盲均衡算法,以达到收敛速度快,稳态误差低的目的。不求助于训练序列的信道均衡称为盲均衡。 CMA(恒定模量算法)和MCMA(改进的恒定模量算法)是用于QAM系统盲均衡的两个广泛引用的算法。与常规均衡方案中采用的算法相比,这些算法表现出非常慢的收敛速度和较大的稳态均方误差。为了获得更好的结果,我们根据均衡器输出端的误差估计在MCMA中使用了变化的步长。仿真结果表明,与CMA和MCMA算法相比,该算法具有更高的收敛速度和更低的稳态误差。

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