An adaptive decision feedback equalizer based on the combination of the FIR and FLNN

作者：Zhao Haiquan^*; Zeng Xiangping; Zhang Xiaoqiang; Zhang Jiashu; Liu Yangguang; Wei Tiao

来源：Digital Signal Processing, 2011, 21(6): 679-689.

DOI：10.1016/j.dsp.2011.05.004

• Adaptive nonlinear equalizer
• Time-variant channel
• Decision feedback
• Functional link neural network

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 RBF) neural network and linear equalizer with decision feedback (LMSDFE) for time-invariant and time-variant nonlinear channel models in digital communication systems.

• 出版日期2011-12
• 单位西南交通大学; 成都信息工程大学; 浙江大学; 浙江大学宁波理工学院