An adaptive decision feedback equalizer based on the combination of the FIR and FLNN |
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| Authors: | Haiquan Zhao Xiangping Zeng Xiaoqiang Zhang Jiashu Zhang Yangguang Liu Tiao Wei[Author vitae] |
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| Affiliation: | aSchool of Electrical Engineering, Southwest Jiaotong University, Chengdu, 610031, China;bSchool of Information Science and Technology, Southwest Jiaotong University, Chengdu, 610031, China;cCenter of Electronic Lab, Chengdu University of Information Technology, Chengdu, 610255, China;dSchool of Transportation and Logistics, Southwest Jiaotong University, Chengdu, 610031, China;eNingbo Institute of Technology, Zhejiang University, Ningbo, 315100, China |
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| Abstract: | To compensate the linear and nonlinear distortions and to track the characteristic of the time-varying channel in digital communication systems, a novel adaptive decision feedback equalizer (DFE) with the combination of finite impulse response (FIR) filter and functional link neural network (CFFLNNDFE) is introduced in this paper. This convex nonlinear combination results in improving the convergence speed while retaining the lower steady-state error at the cost of a small increasing computational burden. To further improve the performance of the nonlinear equalizer, we derive here a novel simplified modified normalized least mean square (SMNLMS) algorithm. Moreover, the convergence properties of the proposed algorithm are analyzed. Finally, computer simulation results which support analysis are provided to evaluate the performance of the proposed equalizer over the functional link neural network (FLNN), radial basis function (RBF) neural network and linear equalizer with decision feedback (LMSDFE) for time-invariant and time-variant nonlinear channel models in digital communication systems. |
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| Keywords: | Adaptive nonlinear equalizer Time-variant channel Decision feedback Functional link neural network |
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