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Information-Theoretically Optimal Compressed Sensing via Spatial Coupling and Approximate Message Passing
, 2011
"... We study the compressed sensing reconstruction problem for a broad class of random, banddiagonal sensing matrices. This construction is inspired by the idea of spatial coupling in coding theory. As demonstrated heuristically and numerically by Krzakala et al. [KMS+ 11], message passing algorithms ca ..."
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Cited by 51 (5 self)
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We study the compressed sensing reconstruction problem for a broad class of random, banddiagonal sensing matrices. This construction is inspired by the idea of spatial coupling in coding theory. As demonstrated heuristically and numerically by Krzakala et al. [KMS+ 11], message passing algorithms can effectively solve the reconstruction problem for spatially coupled measurements with undersampling rates close to the fraction of non-zero coordinates. We use an approximate message passing (AMP) algorithm and analyze it through the state evolution method. We give a rigorous proof that this approach is successful as soon as the undersampling rate δ exceeds the (upper) Rényi information dimension of the signal, d(pX). More precisely, for a sequence of signals of diverging dimension n whose empirical distribution converges to pX, reconstruction is with high probability successful from d(pX) n + o(n) measurements taken according to a band diagonal matrix. For sparse signals, i.e. sequences of dimension n and k(n) non-zero entries, this implies reconstruction from k(n)+o(n) measurements. For ‘discrete ’ signals, i.e. signals whose coordinates take a fixed finite set of values, this implies reconstruction from o(n) measurements. The result
The effect of spatial coupling on compressive sensing
- in Communication, Control, and Computing (Allerton
"... Abstract — Recently, it was observed that spatially-coupled LDPC code ensembles approach the Shannon capacity for a class of binary-input memoryless symmetric (BMS) channels. The fundamental reason for this was attributed to a threshold saturation phenomena derived in [1]. In particular, it was show ..."
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Cited by 46 (9 self)
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Abstract — Recently, it was observed that spatially-coupled LDPC code ensembles approach the Shannon capacity for a class of binary-input memoryless symmetric (BMS) channels. The fundamental reason for this was attributed to a threshold saturation phenomena derived in [1]. In particular, it was shown that the belief propagation (BP) threshold of the spatially coupled codes is equal to the maximum a posteriori (MAP) decoding threshold of the underlying constituent codes. In this sense, the BP threshold is saturated to its maximum value. Moreover, it has been empirically observed that the same phenomena also occurs when transmitting over more general classes of BMS channels. In this paper, we show that the effect of spatial coupling is not restricted to the realm of channel coding. The effect of coupling also manifests itself in compressed sensing. Specifically, we show that spatially-coupled measurement matrices have an improved sparsity to sampling threshold for reconstruction algorithms based on verification decoding. For BP-based reconstruction algorithms, this phenomenon is also tested empirically via simulation. At the block lengths accessible via simulation, the effect is quite small and it seems that spatial coupling is not providing the gains one might expect. Based on the threshold analysis, however, we believe this warrants further study. I.
Improvement of bpbased cdma multiuser detection by spatial coupling
- 2011, coRR
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A simple proof of threshold saturation for coupled scalar recursions
- in Proc. Intl. Symp. on Turbo Codes and Iter. Inform. Proc. (ISTC), 2012
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Universal codes for the gaussian mac via spatial coupling
- in Proc. 49th Ann. Allerton Conf. Comm. Control Comput
"... Abstract—We consider transmission of two independent and separately encoded sources over a two-user binary-input Gaus-sian multiple-access channel. The channel gains are assumed to be unknown at the transmitter and the goal is to design an encoder-decoder pair that achieves reliable communication fo ..."
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Cited by 8 (2 self)
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Abstract—We consider transmission of two independent and separately encoded sources over a two-user binary-input Gaus-sian multiple-access channel. The channel gains are assumed to be unknown at the transmitter and the goal is to design an encoder-decoder pair that achieves reliable communication for all channel gains where this is theoretically possible. We call such a system universal with respect to the channel gains. Kudekar et al. recently showed that terminated low-density parity-check convolutional codes (a.k.a. spatially-coupled low-density parity-check ensembles) have belief-propagation thresh-olds that approach their maximum a-posteriori thresholds. This was proven for binary erasure channels and shown empirically for binary memoryless symmetric channels. It was conjectured that the principle of spatial coupling is very general and the phenomenon of threshold saturation applies to a very broad class of graphical models. In this work, we derive an area theorem for the joint decoder and empirically show that threshold saturation occurs for this problem. As a result, we demonstrate near-universal performance for this problem using the proposed spatially-coupled coding system. Index Terms—Gaussian MAC, LDPC codes, spatial coupling, EXIT functions, density evolution, joint decoding, protograph, area theorem. I.
Threshold saturation in spatially coupled constraint satisfaction problems
- J. Stat. Phys
, 2012
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