Blind Synchronization and Estimation for PN Code of NPLC-DSSS Signal

Zhaoyang QIU; Tianyun LI; Xiong ZHA

doi:10.11999/JEIT200545

Volume 43 Issue 8

Aug. 2021

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Zhaoyang QIU, Tianyun LI, Xiong ZHA. Blind Synchronization and Estimation for PN Code of NPLC-DSSS Signal[J]. Journal of Electronics & Information Technology, 2021, 43(8): 2171-2180. doi: 10.11999/JEIT200545

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Zhaoyang QIU, Tianyun LI, Xiong ZHA. Blind Synchronization and Estimation for PN Code of NPLC-DSSS Signal[J]. Journal of Electronics & Information Technology, 2021, 43(8): 2171-2180. doi: 10.11999/JEIT200545

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Blind Synchronization and Estimation for PN Code of NPLC-DSSS Signal

doi: 10.11999/JEIT200545

Institute of Information Systems Engineering, Information Engineering University, Zhengzhou 450001, China

Funds: The National Natural Science Foundation of China (61401511, U1736107)

Received Date: 2020-07-03
Rev Recd Date: 2020-11-10

Available Online: 2020-12-11

Publish Date: 2021-08-10

Abstract

Abstract

Synchronization and estimation for Pseudo Noise (PN) code of non-cooperative Direct Sequence Spread Spectrum(DSSS)system is the key to obtain the information correctly. Previous works mostly concentrate on Short or Periodic Long Code DSSS(SC-DSSS, PLC-DSSS)signal. Aiming at the estimation for out-of-step time of Non-Periodic Long Code DSSS (NPLC-DSSS) signal without the prior knowledge about the PN code, a distribution modeling-based method for the elements of correlation matrix is proposed. The auto-correlation matrix of information-bit-long segments is constructed and the accurate estimation for out-of-step time is achieved according to the Frobenius norm as a function of out-of-step time. On this basis, by introducing decision aided idea, the cyclic iterative structure is constructed to realize a blind estimation for PN sequence of NPLC-DSSS signal. Finally, the Cramer-Rao Bound (CRB) for the blind PN code estimation problem is derived. Numerical analysis results demonstrate that the proposed method can achieve better estimation accuracy in the same signal to noise ratio and data volume condition and the performance is close to the theoretical bound.

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References(21)

References

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