Sm. Mo et B. Shafai, BLIND EQUALIZATION USING HIGHER-ORDER CUMULANTS AND NEURAL-NETWORK, IEEE transactions on signal processing, 42(11), 1994, pp. 3209-3217
This paper develops a new method to achieve blind equalization in digi
tal communication for linear finite impulse response (FIR) systems, wh
ether the systems are minimum phase or not. This new approach divides
the problem into two parts. First, it employs the characteristic of th
e linear system to estimate the original channel based on the fourth-o
rder cumulants instead of time samples of the channel output. Thus, no
nminimum phase channels can be handled. Second, it utilizes the nonlin
ear characteristics of the neural network to build an inverse system (
equalizer) for the original channel. This is done by using the estimat
ed channel as a reference system to train the neural network. The neur
al network helps the equalizer to reduce the degree of model uncertain
ty and makes the equalizer resistant to additive noise. Taking the adv
antages of both linear and nonlinear systems, this new scheme works we
ll for both stationary and nonstationary cases and leads to good equal
ization results.