CLC number: TN92
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 0000-00-00
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CHEN Rong, ZHANG Hai-bin, XU You-yun, LIU Xin-zhao. Blind receiver for OFDM systems via sequential Monte Carlo in factor graphs[J]. Journal of Zhejiang University Science A, 2007, 8(1): 1-9.
@article{title="Blind receiver for OFDM systems via sequential Monte Carlo in factor graphs",
author="CHEN Rong, ZHANG Hai-bin, XU You-yun, LIU Xin-zhao",
journal="Journal of Zhejiang University Science A",
volume="8",
number="1",
pages="1-9",
year="2007",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2007.A0001"
}
%0 Journal Article
%T Blind receiver for OFDM systems via sequential Monte Carlo in factor graphs
%A CHEN Rong
%A ZHANG Hai-bin
%A XU You-yun
%A LIU Xin-zhao
%J Journal of Zhejiang University SCIENCE A
%V 8
%N 1
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%@ 1673-565X
%D 2007
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2007.A0001
TY - JOUR
T1 - Blind receiver for OFDM systems via sequential Monte Carlo in factor graphs
A1 - CHEN Rong
A1 - ZHANG Hai-bin
A1 - XU You-yun
A1 - LIU Xin-zhao
J0 - Journal of Zhejiang University Science A
VL - 8
IS - 1
SP - 1
EP - 9
%@ 1673-565X
Y1 - 2007
PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.2007.A0001
Abstract: Estimation and detection algorithms for orthogonal frequency division multiplexing (OFDM) systems can be developed based on the sum-product algorithms, which operate by message passing in factor graphs. In this paper, we apply the sampling method (Monte Carlo) to factor graphs, and then the integrals in the sum-product algorithm can be approximated by sums, which results in complexity reduction. The blind receiver for OFDM systems can be derived via sequential Monte Carlo (SMC) in factor graphs, the previous SMC blind receiver can be regarded as the special case of the sum-product algorithms using sampling methods. The previous SMC blind receiver for OFDM systems needs generating samples of the channel vector assuming the channel has an a priori Gaussian distribution. In the newly-built blind receiver, we generate samples of the virtual-pilots instead of the channel vector, with channel vector which can be easily computed based on virtual-pilots. As the size of the virtual-pilots space is much smaller than the channel vector space, only small number of samples are necessary, with the blind detection being much simpler. Furthermore, only one pilot tone is needed to resolve phase ambiguity and differential encoding is not used anymore. Finally, the results of computer simulations demonstrate that the proposal can perform well while providing significant complexity reduction.
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