Joint Estimation of Spreading Codes and Information Sequences for Asynchronous Long Code DS-CDMA Signals Based on Sequential Monte Carlo

Zhaogen ZHONG; Keyuan YU; Xueli SUN

doi:10.11999/JEIT180157

Volume 41 Issue 6

Jun. 2019

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Article Navigation > Journal of Electronics & Information Technology > 2019 > 41(6): 1365-1373

Zhaogen ZHONG, Keyuan YU, Xueli SUN. Joint Estimation of Spreading Codes and Information Sequences for Asynchronous Long Code DS-CDMA Signals Based on Sequential Monte Carlo[J]. Journal of Electronics & Information Technology, 2019, 41(6): 1365-1373. doi: 10.11999/JEIT180157

Citation:

Zhaogen ZHONG, Keyuan YU, Xueli SUN. Joint Estimation of Spreading Codes and Information Sequences for Asynchronous Long Code DS-CDMA Signals Based on Sequential Monte Carlo[J]. Journal of Electronics & Information Technology, 2019, 41(6): 1365-1373. doi: 10.11999/JEIT180157

Citation:

Zhaogen ZHONG, Keyuan YU, Xueli SUN. Joint Estimation of Spreading Codes and Information Sequences for Asynchronous Long Code DS-CDMA Signals Based on Sequential Monte Carlo[J]. Journal of Electronics & Information Technology, 2019, 41(6): 1365-1373. doi: 10.11999/JEIT180157

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Joint Estimation of Spreading Codes and Information Sequences for Asynchronous Long Code DS-CDMA Signals Based on Sequential Monte Carlo

doi: 10.11999/JEIT180157

School of Basis of Aviation, Naval Aviation University, Yantai 264001, China

Funds: The National Natural Science Foundation of China (91538201),The Taishan Scholar Special Foundation (201511020)

Received Date: 2018-02-06
Rev Recd Date: 2019-03-12

Available Online: 2019-04-01

Publish Date: 2019-06-01

Abstract

Abstract

To deal with the problem of joint estimation of spreading codes and information sequences for asynchronous long code DS-CDMA signals in multipath channels, an algorithm is introduced based on Sequential Monte Carlo(SMC) for blind estimation. The proposed algorithm emploies hybrid important sampling density to draw the samples from joint posterior distribution iteratively, and computes the importance weight to complete the estimation of the state variable. During the realization of the algorithm, in order to reduce the computational complexity, the modified algorithm estimates the spreading code of each user firstly, then processes the observation data, thereby modifies the original iteration step. Simulation results verify the adaptability of the proposed algorithms for multiple conditions. Moreover, it can obtain good estimation performance in time varying multipath channels.
- Spread spectrum communication,
- Code Division Multiple Access(CDMA),
- Sequential Monte Carlo(SMC),
- Spreading code,
- Information sequence

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References(16)

References

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