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Content Provider | IET Digital Library |
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Author | Shen, Bin Wang, Jian xin |
Abstract | 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. |
Starting Page | 727 |
Ending Page | 733 |
Page Count | 7 |
ISSN | 17519675 |
Volume Number | 11 |
e-ISSN | 17519683 |
Issue Number | Issue 6, Aug (2017) |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/iet-spr/11/6 |
Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/iet-spr.2016.0687 |
Journal | IET Signal Processing |
Publisher Date | 2017-03-16 |
Access Restriction | Open |
Rights Holder | © The Institution of Engineering and Technology |
Subject Keyword | Algebra Chip Rate Code Division Multiple Access Computational Complexity Computer Simulation Correlation Matrix Direct Sequence Spread Spectrum Signal Matrix Algebra Matrix Principal Eigenvector Denoising Multiple Access Communication PN Sequence Estimation Algorithm Pseudonoise Sequence Estimation Radio Link And Equipment Received Signal Sample Signal Denoising Signal Processing And Detection Signal to Noise Ratio Spread Spectrum Communication Temporal Segments Theory Analysis |
Content Type | Text |
Resource Type | Article |
Subject | Signal Processing Electrical and Electronic Engineering |
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