Document Type


Date of Award

Spring 5-31-1994

Degree Name

Master of Science in Electrical Engineering - (M.S.)


Electrical and Computer Engineering

First Advisor

Alexander Haimovich

Second Advisor

Nirwan Ansari

Third Advisor

Zoran Siveski


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 almost white spectral properties, thermal noise, and correlated narrow-band interferences. A new approach is proposed which exploits the statistical properties of the received signal via eigenanalysis of the received data. While the energy of the wide-band signal is distributed over all the eigenvalues of the signal autocorrelation matrix, the energy of the interference is concentrated in a few large eigenvalues. Hence, the eigenvectors corresponding to the large eigenvalues are termed the interference subspace. The proposed method derives a. weight vector residing in the subspace spanned by the rest of the eigenvectors termed the noise subspace. Consequently, it is orthogonal to the interference subspace. The eigenanalysis based interference cancellation is sub-optimal in a known signal environment, but is superior to the Wiener-Hopf filter when the signal statistics are estimated from a limited amount of data. A fast and effective adaptive algorithm is derived using the power method.