Direct sequence data separation using adaptive blind deconvolution

Abstract EN

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