Title :
Multi terminal probabilistic compressed sensing
Author :
Haghighatshoar, Saeid
Author_Institution :
EPFL, Lausanne, Switzerland
fDate :
June 29 2014-July 4 2014
Abstract :
In this paper, the `Approximate Message Passing´ (AMP) algorithm, initially developed for compressed sensing of signals under i.i.d. Gaussian measurement matrices, has been extended to a multi-terminal setting (MAMP algorithm). It has been shown that similar to its single-terminal counterpart, the behavior of MAMP algorithm is fully characterized by a `State Evolution´ (SE) equation for large block-lengths. This equation is used to obtain the rate-distortion curve of a multi-terminal memoryless source. It is observed that by spatially coupling the measurement matrices, the rate-distortion curve of MAMP algorithm undergoes a phase transition, where the measurement rate region corresponding to a low-distortion (approximately zero distortion) regime is fully characterized by the joint and the conditional Rényi information dimension (RID) of the multi-terminal source. This measurement rate region is very similar to the rate region of the Slepian-Wolf distributed source coding problem where the RID plays a role similar to the discrete entropy. Simulations are done to investigate the empirical behavior of MAMP algorithm. It is observed that simulation results match very well with the predictions of SE equation for reasonably large block-lengths.
Keywords :
Gaussian processes; compressed sensing; entropy; memoryless systems; message passing; probability; source coding; Gaussian measurement matrices; MAMP algorithm; Renyi information dimension; Slepian-Wolf distributed source coding problem; approximate message passing algorithm; discrete entropy; low distortion regime; multiterminal memoryless source; multiterminal probabilistic compressed sensing; multiterminal setting; multiterminal source; phase transition; rate distortion curve; state evolution equation; Approximation algorithms; Compressed sensing; Correlation; Distortion measurement; Equations; Mathematical model; Message passing; Approximate message passing (AMP); Gaussian measurement matrices; Multi-terminal (distributed) compressed sensing; Multi-terminal Approximate Message Passing (MAMP); Rényi information dimension; Spatial coupling;
Conference_Titel :
Information Theory (ISIT), 2014 IEEE International Symposium on
Conference_Location :
Honolulu, HI
DOI :
10.1109/ISIT.2014.6874827