Title :
A neural-based digital communication receiver for inter-symbol interference and white Gaussian noise channels
Author :
Bang, Sa H. ; Sheu, Bing J.
Author_Institution :
Univ. of Southern California, Los Angeles, CA, USA
Abstract :
A multilayer perceptron with the extended Kalman filter (EKF) training algorithm is investigated as a communication receiver when intersymbol interference and white Gaussian noise are present. Besides discussing the complexity of the EKF algorithm, it is shown that the EKF has better performance than the conventional backpropagation (BP) training algorithm in the sense that is requires less training steps and also results in proper training even when the BP did not. With 2500 training symbols, the EKF resulted in about 4-dB performance improvement over the conventional BP
Keywords :
Kalman filters; digital communication systems; feedforward neural nets; intersymbol interference; white noise; extended Kalman filter; inter-symbol interference; multilayer perceptron; neural-based digital communication receiver; training algorithm; training symbols; white Gaussian noise channels; Digital communication; Equalizers; Fading; Finite impulse response filter; Gaussian noise; Interference; Maximum likelihood estimation; Multilayer perceptrons; Pulse modulation; Viterbi algorithm;
Conference_Titel :
Circuits and Systems, 1992. ISCAS '92. Proceedings., 1992 IEEE International Symposium on
Conference_Location :
San Diego, CA
Print_ISBN :
0-7803-0593-0
DOI :
10.1109/ISCAS.1992.230636
