DIRECT SEQUENCE DATA SEPARATION USING ADAPTIVE BLIND DECONVOLUTION

Abstract

Direct sequence spread spectrum (DSSS) signal is generated by modulating the pseudo randomnoise (PN) sequence with the data signal. The receiver must generate the same PN sequence toextract the direct sequence signal and then get the data signal. This paper presents a method toseparate the PN sequence and data sequence from DSSS signal using adaptive blind deconvolutiontechnique which utilizes the normalized cumulant of the adaptive signal. To minimize thecomputation burden the process gain is first estimated and is used in the adaptation process. Theprocess gain estimator is also based on the computation of the normalized cumulant. Moreover, anefficient method that can enhance the direct-sequence spread spectrum (DSSS) signal at the receiveris introduced without complicating traditional slipping and tracking schemes. Both theoreticalanalysis and computer simulations verify the validity of the proposed method.