Open AccessChip rate and pseudo‐noise sequence estimation for direct sequence spread spectrum signals
Author(s) -
Shen Bin,
Wang Jianxin
Publication year - 2017
Publication title -
iet signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.384
H-Index - 42
ISSN - 1751-9683
DOI - 10.1049/iet-spr.2016.0687
Subject(s) - computational complexity theory , algorithm , sequence (biology) , noise (video) , eigenvalues and eigenvectors , direct sequence spread spectrum , computer science , signal to noise ratio (imaging) , matrix (chemical analysis) , chip , signal (programming language) , spread spectrum , mathematics , artificial intelligence , telecommunications , code division multiple access , physics , quantum mechanics , biology , image (mathematics) , genetics , materials science , composite material , programming language
This study presents a chip rate and pseudo‐noise (PN) sequence estimation algorithm of direct sequence spread spectrum signals. The received signal samples are divided into temporal segments, from which the correlation matrix is computed and decomposed. Then the principal eigenvector of this matrix is de‐noised. The chip rate and the PN sequence are estimated from the de‐noised principal eigenvector. The computational complexity is also evaluated. Theory analysis and computer simulation results show that, compared with other algorithms, the performance of proposed algorithm is significantly improved at the approximate computational complexity. In addition, an improved version with low computational complexity is available. Simulation results also verify the effectiveness and superior performance of improved algorithm in low signal‐to‐noise ratio.