Blind Estimation of Self-Synchronous Scrambler in DSSS Systems
2021
Self-synchronous scramblers are more difficult to blindly estimate than synchronous scramblers because their input sequence affects the state of the scrambler’s linear feedback shift register. There has been much research on the estimation of synchronous scramblers and relatively little on the estimation of self-synchronous scramblers. For non-cooperative contexts, this paper proposes a method for the estimation of a self-synchronous scrambler in direct sequence spread spectrum systems. We blindly estimate the self-synchronous scrambling parameter, the feedback polynomial, using the repeated patterns by a spreading code, the linearity between the bits in a scrambling sequence, and the coidentity of the self-synchronous scrambled sequence and the linear feedback shift register states. To validate the proposed method, we show the estimation performance in terms of the computational complexity, required minimum scrambled sequence length, execution time, and detection probability.
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