A blind equalization algorithm based on bilinear recurrent neural network
暂无分享,去创建一个
In this paper, we propose a new blind equalization algorithm based on bilinear recurrent neural network. In the first part, a new transmission function and cost function is designed for the neural network. In the second part, the new neural network is used to blind equalization algorithm. Results of the simulation show that our algorithm can obtains better convergence performance and lower bit error rate (BER) than traditional constant modulus algorithm (CMA).
[1] J. Treichler,et al. A new approach to multipath correction of constant modulus signals , 1983 .
[2] Rodney A. Kennedy,et al. Convex cost functions in blind equalization , 1994, IEEE Trans. Signal Process..
[3] Dong-Chul Park,et al. Complex-bilinear recurrent neural network for equalization of a digital satellite channel , 2002, IEEE Trans. Neural Networks.
[4] Zhang Ning. A blind equalization algorithm for FPGA realization , 2001 .