DIRECT SEQUENCE DATA SEPARATION USING ADAPTIVE BLIND DECONVOLUTION

Abdel Rahem, Gamal M. M.; Sayed Mohammed, Usama; Sherif, Khaled S.

doi:10.21608/jesaun.2015.115169

DIRECT SEQUENCE DATA SEPARATION USING ADAPTIVE BLIND DECONVOLUTION

Document Type : Research Paper

Authors

¹ Electrical Engineering Department, Faculty of Engineering, Assiut University, Assiut, Egypt

² Electrical Engineering Department,Faculty of Engineering,Assiut University, Assiut, Egypt

10.21608/jesaun.2015.115169

Abstract

Direct sequence spread spectrum (DSSS) signal is generated by modulating the pseudo random
noise (PN) sequence with the data signal. The receiver must generate the same PN sequence to
extract the direct sequence signal and then get the data signal. This paper presents a method to
separate the PN sequence and data sequence from DSSS signal using adaptive blind deconvolution
technique which utilizes the normalized cumulant of the adaptive signal. To minimize the
computation burden the process gain is first estimated and is used in the adaptation process. The
process gain estimator is also based on the computation of the normalized cumulant. Moreover, an
efficient method that can enhance the direct-sequence spread spectrum (DSSS) signal at the receiver
is introduced without complicating traditional slipping and tracking schemes. Both theoretical
analysis and computer simulations verify the validity of the proposed method.

Keywords