Orthogonal Approximate Message-Passing for Spatially Coupled Systems

10/12/2022
by   Keigo Takeuchi, et al.
0

Orthogonal approximate message-passing (OAMP) is proposed for signal recovery from right-orthogonally invariant linear measurements with spatial coupling. Conventional state evolution is generalized to a unified framework of state evolution for the spatial coupling and long-memory case. The unified framework is used to formulate the so-called Onsager correction in OAMP for spatially coupled systems. The state evolution recursion of Bayes-optimal OAMP is proved to converge for spatially coupled systems via Bayes-optimal long-memory OAMP and its state evolution. This paper proves the information-theoretic optimality of Bayes-optimal OAMP for noiseless spatially coupled systems with right-orthogonally invariant sensing matrices.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
10/13/2022

Long-Memory Message-Passing for Spatially Coupled Systems

This paper addresses the reconstruction of sparse signals from spatially...
research
11/10/2021

On the Convergence of Orthogonal/Vector AMP: Long-Memory Message-Passing Strategy

Orthogonal/vector approximate message-passing (AMP) is a powerful messag...
research
01/10/2019

A Unified Framework of State Evolution for Message-Passing Algorithms

This paper presents a unified framework to understand the dynamics of me...
research
10/12/2021

Generalized Memory Approximate Message Passing

Generalized approximate message passing (GAMP) is a promising technique ...
research
12/06/2018

Rank-one matrix estimation: analysis of algorithmic and information theoretic limits by the spatial coupling method

Factorizing low-rank matrices is a problem with many applications in mac...
research
12/31/2021

Sufficient Statistic Memory AMP

Approximate message passing (AMP) is a promising technique for unknown s...
research
05/26/2022

Multi-layer State Evolution Under Random Convolutional Design

Signal recovery under generative neural network priors has emerged as a ...

Please sign up or login with your details

Forgot password? Click here to reset