Blind Estimation of a Scrambler in Long-Code Direct Sequence Spread Spectrum Systems

Abstract

Recently, a method for blind estimation of a scrambler in a short-code DSSS system has been studied, applying the removal of the message and spreading code from the scrambled signal. However, this method does not perform well in long-code DSSS systems where the length of the spreading code and the spreading factor are different, making it difficult to remove messages from the scrambled signal. This paper presents a scrambler estimation algorithm that extends the existing method to be applicable in long-code DSSS systems. To achieve this, we first remove the message from the scrambled DSSS signal by considering the spreading factor and then generate candidates for the multiples of the feedback polynomial of the scrambler based on the internal linearity. Subsequently, the correct feedback polynomial of the scrambler is determined from the generated candidates through an examination of the linearity in the received signals and the polynomial factorization algorithm. Through computer simulations, we validate that the proposed algorithm can estimate the feedback polynomial of the scrambler in long-code DSSS systems.