• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.115-121
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• 2019

In this paper, we propose MSAG-SCS-MMA-I adaptive blind equalization with double step size with very small residual ISI and MSE at steady-state while significantly improving the convergence speed of the traditional SCS-MMA-I algorithm in 256-QAM system. And we evaluate the equalization performance for this algorithm. Different step sizes according to the absolute value of decision-directed error instead of a fixed step-size are applied to the tap update equation of MSAG-SCS-MMA-I, which is controlled by binary flags of '1' or '0' obtained from SCS-MMA-I and decision-directed algorithms. This makes for excellent equalization performance. As a result of computer simulation, we confirmed that the proposed algorithm has more better performance than the MMA, SCS-MMA-I, and MSAG-SCS-MMA-I algorithms in terms of the performance index such as residual ISI, MSE, and MD.