Rejection of narrow-band interferences in PN spread spectrum systems using an eigenanalysis approach

A new adaptive technique is suggested for rejecting narrow-band interferences in spread spectrum communications. When data is coded using a pseudo-noise code, the received signal consists of a wide-band signal with an almost white spectrum, and correlated narrow-band interference. The conventional approach to the interference suppression has been to exploit this correlation property to minimize the mean square error between predicted values of the signal and actual observations. The optimal solution is given by the Wiener filter. A different approach is suggested by the eigenanalysis of the data across the filter taps. While the energy of the spread spectrum signal is distributed across all the eigenvalues of the data correlation matrix, the energy of the interference is concentrated in a few large eigenvalues. The corresponding eigenvectors span the same signal subspace as the interference. The proposed method derives an error prediction filter with the additional constraint of orthogonality to these eigenvectors. The eigenanalysis based interference cancellation is sub-optimal for known correlation matrix, but is superior to the Wiener filter when the correlation matrix is estimated from a limited amount of data.