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A Fast Convergent Algorithm for Semi-Blind Equalization

机译:半盲均衡的快速收敛算法

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摘要

To overcome the disadvantages that the Constant Modulus Algorithm (CMA) and Modified Constant Modulus Algorithm (MCMA) is of low convergence rate, a fast convergent algorithm for semi-blind equalization is presented. We use the CMA and MCMA to perform channel equalization, and adopt LMS algorithm with decision to compensate CMA and MCMA respectively. Simulations, which are done under linear channel and nonlinear channel respectively, indicate that convergence rate of the new algorithm is four times faster than that of Constant Modulus Algorithm and Modified Constant Modulus Algorithm under linear channel. In case of nonlinear channel, the convergence speed of this new semi-blind equalization algorithm is also four times faster than that of Modified Constant Modulus Algorithm.
机译:针对恒模量算法和改进恒模量算法收敛速度慢的缺点,提出了一种半盲均衡的快速收敛算法。我们使用CMA和MCMA进行信道均衡,并采用具有决定权的LMS算法分别补偿CMA和MCMA。分别在线性信道和非线性信道下进行的仿真表明,新算法的收敛速度比线性信道下的恒模算法和改进的恒模算法快四倍。在非线性信道的情况下,这种新的半盲均衡算法的收敛速度也比改进的恒定模量算法快四倍。

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