Bayes-Optimal Convolutional AMP
نویسندگان
چکیده
This paper proposes Bayes-optimal convolutional approximate message-passing (CAMP) for signal recovery in compressed sensing. CAMP uses the same low-complexity matched filter (MF) interference suppression as (AMP). To improve convergence property of AMP ill-conditioned sensing matrices, so-called Onsager correction term is replaced by a convolution all preceding messages. The tap coefficients are determined so to realize asymptotic Gaussianity estimation errors via state evolution (SE) under assumption orthogonally invariant matrices. An SE equation derived optimize sequence denoisers CAMP. optimized proved be matrices if converges fixed-point and unique. For with low-to-moderate condition numbers, can achieve performance high-complexity orthogonal/vector that requires linear minimum mean-square error (LMMSE) instead MF.
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ژورنال
عنوان ژورنال: IEEE Transactions on Information Theory
سال: 2021
ISSN: ['0018-9448', '1557-9654']
DOI: https://doi.org/10.1109/tit.2021.3077471