2016/01/22 by Zhengdao Yuan, Chuanzong Zhang, Yuan, Zhengdao +9
Computer Science · Engineering · Mathematics · #Advanced Wireless Communication Techniques #Blind Source Separation Techniques #Error Correcting Code Techniques #FOS: Computer and information sciences #Information Theory (cs.IT) #cs.IT #math.IT
paper · pdf · doi:10.48550/arxiv.1601.05856
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openalex publication_date 2016/01/22 · arxiv created 2017/11/10 · arxiv updated 2017/11/13 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
With a unified belief propagation (BP) and mean field (MF) framework, we propose an iterative message passing receiver, which performs joint channel state and noise precision (the reciprocal of noise variance) estimation and decoding for OFDM systems. The recently developed generalized approximate message passing (GAMP) is incorporated to the BP-MF framework, where MF is used to handle observation factor nodes with unknown noise precision and GAMP is used for channel estimation in the time-frequency domain. Compared to state-of-the-art algorithms in the literature, the proposed algorithm either delivers similar performance with much lower complexity, or delivers much better performance with similar complexity. In addition, the proposed algorithm exhibits fastest convergence.