Abstract：An adaptive blind channel identification algorithm was proposed based on the modulation induced second-order cyclostationarity. The cyclic correlation matrix was updated by means of updating cyclic autocorrelation functions at different time lags. Then the conjugate gradient descent method was used to realize adaptive blind identification of the channel, and the time-varying step size is presented for the determination of optimal step size in each iteration. The proposed algorithm has the property of simplicity and good restraint on stationary colored noise due to using the second-order cyclic statistics. Computer simulations show the effectiveness of proposed adaptive algorithm under low signal to noise ratio.
2010, Vol. 29 
