An Integral-Based Approach to Orthogonal AMP

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

3 Scopus Citations
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Detail(s)

Original languageEnglish
Pages (from-to)194-198
Journal / PublicationIEEE Signal Processing Letters
Volume28
Online published24 Dec 2020
Publication statusPublished - 2021

Abstract

Approximate message passing (AMP) is an iterative signal recovery algorithm for compressive sensing (CS) applications. In this letter, we present an integral-based orthogonal AMP (IB-OAMP) technique that avoids the requirements of AMP (and also the original form of OAMP) on differentiable and separable denoisers. The orthogonality in IB-OAMP can be established using a Monte Carlo method similar to the training stage in a machine-learning algorithm. These features make IB-OAMP attractive to be used in conjunction with some well-studied denoising algorithms.

Research Area(s)

  • Binary phase shift keying, Gram-Schmidt orthogonality, integral-based OAMP, Monte Carlo methods, Noise reduction, Orthogonal approximate message passing, Sensors, Signal processing algorithms, Software algorithms, state evolution, Training

Citation Format(s)

An Integral-Based Approach to Orthogonal AMP. / Cheng, Yiyao; Liu, Lei; Ping, Li.
In: IEEE Signal Processing Letters, Vol. 28, 2021, p. 194-198.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review