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Detection of Nonlinearly Distorted M-ary QAM Signals Using Self-Organizing Map
Xiaoqiu WANG Hua LIN Jianming LU Takashi YAHAGI
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Publication Date: 2001/08/01
Print ISSN: 0916-8508
Type of Manuscript: Special Section PAPER (Special Section on Digital Signal Processing)
Category: Applications of Signal Processing
self-organizing map, winning neuron, decision feedback equalization, quadrature amplitude modulation,
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Detection of nonlinearly distorted signals is an essential problem in telecommunications. Recently, neural network combined conventional equalizer has been used to improve the performance especially in compensating for nonlinear distortions. In this paper, the self-organizing map (SOM) combined with the conventional symbol-by-symbol detector is used as an adaptive detector after the output of the decision feedback equalizer (DFE), which updates the decision levels to follow up the nonlinear distortions. In the proposed scheme, we use the box distance to define the neighborhood of the winning neuron of the SOM algorithm. The error performance has been investigated in both 16 QAM and 64 QAM systems with nonlinear distortions. Simulation results have shown that the system performance is remarkably improved by using SOM detector compared with the conventional DFE scheme.