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A BP–MF–EP based iterative receiver for joint phase noise estimation, equalization, and decoding

Journal Article


Abstract


  • In this letter, with combined belief propagation (BP), mean field (MF), and expectation propagation (EP), an iterative receiver is designed for joint phase noise estimation, equalization, and decoding in a coded communication system. The presence of the phase noise results in a nonlinear observation model. Conventionally, the nonlinear model is directly linearized by using the first-order Taylor approximation, e.g., in the state-of-the-art soft-input extended Kalman smoothing approach (Soft-in EKS). In this letter, MF is used to handle the factor due to the nonlinear model, and a second-order Taylor approximation is used to achieve Gaussian approximation to the MF messages, which is crucial to the low-complexity implementation of the receiver with BP and EP. It turns out that our approximation is more effective than the direct linearization in the Soft-in EKS, leading to a significant performance improvement with similar complexity as demonstrated by simulation results.

UOW Authors


  •   Wang, Wei (external author)
  •   Wang, Zhongyong (external author)
  •   Zhang, Chuanzong (external author)
  •   Guo, Qinghua
  •   Sun, Peng (external author)
  •   Wang, Xingye (external author)

Publication Date


  • 2016

Citation


  • W. Wang, Z. Wang, C. Zhang, Q. Guo, P. Sun & X. Wang, "A BP–MF–EP based iterative receiver for joint phase noise estimation, equalization, and decoding,"^^ IEEE Signal Processing Letters, vol. 23, (10) pp. 1349-1353, 2016.

Scopus Eid


  • 2-s2.0-84986192060

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/5996

Number Of Pages


  • 4

Start Page


  • 1349

End Page


  • 1353

Volume


  • 23

Issue


  • 10

Place Of Publication


  • United States

Abstract


  • In this letter, with combined belief propagation (BP), mean field (MF), and expectation propagation (EP), an iterative receiver is designed for joint phase noise estimation, equalization, and decoding in a coded communication system. The presence of the phase noise results in a nonlinear observation model. Conventionally, the nonlinear model is directly linearized by using the first-order Taylor approximation, e.g., in the state-of-the-art soft-input extended Kalman smoothing approach (Soft-in EKS). In this letter, MF is used to handle the factor due to the nonlinear model, and a second-order Taylor approximation is used to achieve Gaussian approximation to the MF messages, which is crucial to the low-complexity implementation of the receiver with BP and EP. It turns out that our approximation is more effective than the direct linearization in the Soft-in EKS, leading to a significant performance improvement with similar complexity as demonstrated by simulation results.

UOW Authors


  •   Wang, Wei (external author)
  •   Wang, Zhongyong (external author)
  •   Zhang, Chuanzong (external author)
  •   Guo, Qinghua
  •   Sun, Peng (external author)
  •   Wang, Xingye (external author)

Publication Date


  • 2016

Citation


  • W. Wang, Z. Wang, C. Zhang, Q. Guo, P. Sun & X. Wang, "A BP–MF–EP based iterative receiver for joint phase noise estimation, equalization, and decoding,"^^ IEEE Signal Processing Letters, vol. 23, (10) pp. 1349-1353, 2016.

Scopus Eid


  • 2-s2.0-84986192060

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/5996

Number Of Pages


  • 4

Start Page


  • 1349

End Page


  • 1353

Volume


  • 23

Issue


  • 10

Place Of Publication


  • United States