A BP-MF-EP Based Iterative Receiver for Joint Phase Noise Estimation, Equalization, and Decoding

W. Wang, Z. Wang, C. Zhang, Qinghua Guo, P. Sun, X. Wang

    Research output: Contribution to journalArticle

    2 Citations (Scopus)

    Abstract

    © 2016 IEEE.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.
    Original languageEnglish
    Pages (from-to)1349-1353
    JournalIEEE Signal Processing Letters
    Volume23
    Issue number10
    DOIs
    Publication statusPublished - 2016

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