@inproceedings{Olmos2015b,

title = {Analyzing the Finite-Length Performance of Generalized LDPC Codes},

author = {Pablo M Olmos and David G M Mitchell and Daniel J Costello},

url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7282943},

doi = {10.1109/ISIT.2015.7282943},

isbn = {978-1-4673-7704-1},

year  = {2015},

date = {2015-06-01},

booktitle = {2015 IEEE International Symposium on Information Theory (ISIT)},

pages = {2683--2687},

publisher = {IEEE},

address = {Hong Kong},

abstract = {In this paper, we analyze the performance of finite-length generalized LDPC (GLDPC) block codes constructed from protographs when transmission takes place over the binary erasure channel (BEC). A generalized peeling decoder is proposed and we derive a system of differential equations that gives the expected evolution of the graph degree distribution during decoding. We then show that the finite-length performance of a GLDPC code can be estimated by means of a simple scaling law, where a single scaling parameter represents the finite-length properties of the code. We also show that, as we consider stronger component codes, both the asymptotic threshold and the finite-length scaling parameter are improved.},

keywords = {BEC, binary codes, binary erasure channel, Block codes, Codes on graphs, Decoding, Differential equations, error probability, finite-length generalized LDPC block codes, finite-length performance analysis, generalized LDPC codes, generalized peeling decoder, GLDPC block codes, graph degree distribution, graph theory, Iterative decoding, parity check codes, protographs},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Stinner2015,

title = {Finite-Length Performance of Multi-Edge Protograph-Based Spatially Coupled LDPC Codes},

author = {Markus Stinner and Pablo M Olmos},

url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7282583},

doi = {10.1109/ISIT.2015.7282583},

isbn = {978-1-4673-7704-1},

year  = {2015},

date = {2015-06-01},

booktitle = {2015 IEEE International Symposium on Information Theory (ISIT)},

pages = {889--893},

publisher = {IEEE},

address = {Hong Kong},

abstract = {The finite-length performance of multi-edge spatially coupled low-density parity-check (SC-LDPC) codes over the binary erasure channel (BEC) is analyzed. Existing scaling laws are extended to arbitrary protograph base matrices that include puncturing patterns and multiple edges between nodes. A regular protograph-based SC-LDPC construction based on the (4; 8)-regular LDPC block code works well in the waterfall region compared to more involved rate-1/2 structures proposed to improve the threshold to minimum distance trade-off. Scaling laws are also used for code design and to estimate the block length of a given SC-LDPC code ensemble to match the performance of some other code. Estimates on the performance degradation are developed if the chain length varies.},

keywords = {binary erasure channel, Block codes, Couplings, Decoding, Error analysis, finite length performance, finite-length performance, graph theory, Iterative decoding, low density parity check codes, multiedge protograph, parity check codes, spatially coupled LDPC codes, spatially-coupled LDPC codes, Steady-state},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Cespedes2014b,

title = {Improved Performance of LDPC-Coded MIMO Systems with EP-based Soft-Decisions},

author = {Javier Cespedes and Pablo M Olmos and Matilde Sanchez-Fernandez and Fernando Perez-Cruz},

url = {http://ieeexplore.ieee.org/articleDetails.jsp?arnumber=6875183},

isbn = {978-1-4799-5186-4},

year  = {2014},

date = {2014-01-01},

booktitle = {2014 IEEE International Symposium on Information Theory},

pages = {1997--2001},

publisher = {IEEE},

address = {Honolulu},

abstract = {Modern communications systems use efficient encoding schemes, multiple-input multiple-output (MIMO) and high-order QAM constellations for maximizing spectral efficiency. However, as the dimensions of the system grow, the design of efficient and low-complexity MIMO receivers possesses technical challenges. Symbol detection can no longer rely on conventional approaches for posterior probability computation due to complexity. Marginalization of this posterior to obtain per-antenna soft-bit probabilities to be fed to a channel decoder is computationally challenging when realistic signaling is used. In this work, we propose to use Expectation Propagation (EP) algorithm to provide an accurate low-complexity Gaussian approximation to the posterior, easily solving the posterior marginalization problem. EP soft-bit probabilities are used in an LDPC-coded MIMO system, achieving outstanding performance improvement compared to similar approaches in the literature for low-complexity LDPC MIMO decoding.},

keywords = {Approximation algorithms, Approximation methods, approximation theory, Channel Coding, channel decoder, communication complexity, complexity, Complexity theory, Detectors, encoding scheme, EP soft bit probability, EP-based soft decision, error statistics, expectation propagation, expectation-maximisation algorithm, expectation-propagation algorithm, Gaussian approximation, Gaussian channels, LDPC, LDPC coded MIMO system, Low Complexity receiver, MIMO, MIMO communication, MIMO communication systems, MIMO receiver, modern communication system, multiple input multiple output, parity check codes, per-antenna soft bit probability, posterior marginalization problem, posterior probability computation, QAM constellation, Quadrature amplitude modulation, radio receivers, signaling, spectral analysis, spectral efficiency maximization, symbol detection, telecommunication signalling, Vectors},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Stinner2014,

title = {Analyzing Finite-length Protograph-Based Spatially Coupled LDPC Codes},

author = {Markus Stinner and Pablo M Olmos},

url = {http://ieeexplore.ieee.org/articleDetails.jsp?arnumber=6874961},

isbn = {978-1-4799-5186-4},

year  = {2014},

date = {2014-01-01},

booktitle = {2014 IEEE International Symposium on Information Theory},

pages = {891--895},

publisher = {IEEE},

address = {Honolulu},

abstract = {The peeling decoding for spatially coupled low-density parity-check (SC-LDPC) codes is analyzed for a binary erasure channel. An analytical calculation of the mean evolution of degree-one check nodes of protograph-based SC-LDPC codes is given and an estimate for the covariance evolution of degree-one check nodes is proposed in the stable decoding phase where the decoding wave propagates along the chain of coupled codes. Both results are verified numerically. Protograph-based SC-LDPC codes turn out to have a more robust behavior than unstructured random SC-LDPC codes. Using the analytically calculated parameters, the finite-length scaling laws for these constructions are given and verified by numerical simulations.},

keywords = {binary erasure channel, covariance analysis, covariance evolution, Decoding, degree-one check nodes, Error analysis, finite-length protograph, mean evolution, Monte Carlo methods, parity check codes, peeling decoding, protograph-based SC-LDPC codes, spatially coupled low-density parity-check codes, stable decoding phase, Steady-state, Vectors},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Olmos2014,

title = {Improving the Finite-Length Performance of Long SC-LDPC Code Chains by Connecting Consecutive Chains},

author = {Pablo M Olmos and David G M Mitchell and Dimitri Truhachev and Daniel J Costello},

url = {http://ieeexplore.ieee.org/articleDetails.jsp?arnumber=6955088},

year  = {2014},

date = {2014-01-01},

booktitle = {8th IEEE International Symposium on Turbo Codes \& Iterative Information Processing},

pages = {72--76},

publisher = {IEEE},

address = {Bremen},

abstract = {We propose a novel encoding/transmission scheme called continuous chain (CC) transmission that is able to improve the finite-length performance of a system using long spatially coupled low-density parity-check (SC-LDPC) code chains. First, we show that the decoding of SC-LDPC code chains is more reliable for shorter chain lengths, i.e., the scaling between block error rate and gap to threshold is more favorable for shorter chains. This motivates the use of CC transmission in which, instead of transmitting a sequence of independent codewords from a long SC-LDPC chain, we connect multiple chains in a layered format, where encoding, transmission, and decoding are now performed in a continuous fashion. Finally, we show that CC transmission can be implemented with only a small increase in decoding complexity or delay with respect to a system employing a single SC-LDPC code chain for transmission},

keywords = {Decoding, Error analysis, error probability, Information processing, parity check codes, Turbo codes},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Salamanca2013,

title = {Improving the BP Estimate over the AWGN Channel Using Tree-Structured Expectation Propagation},

author = {Luis Salamanca and Juan Jose Murillo-Fuentes and Pablo M Olmos and Fernando Perez-Cruz},

url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6620774},

issn = {2157-8095},

year  = {2013},

date = {2013-01-01},

booktitle = {2013 IEEE International Symposium on Information Theory},

pages = {2990--2994},

publisher = {IEEE},

address = {Istanbul},

abstract = {In this paper, we propose the tree-structured expectation propagation (TEP) algorithm for low-density parity-check (LDPC) decoding over the binary additive white Gaussian noise (BI-AWGN) channel. By approximating the posterior distribution by a tree-structure factorization, the TEP has been proven to improve belief propagation (BP) decoding over the binary erasure channel (BEC). We show for the AWGN channel how the TEP decoder is also able to capture additional information disregarded by the BP solution, which leads to a noticeable reduction of the error rate for finite-length codes. We show that for the range of codes of interest, the TEP gain is obtained with a slight increase in complexity over that of the BP algorithm. An efficient way of constructing the tree-like structure is also described.},

keywords = {Approximation algorithms, Approximation methods, AWGN channels, BEC, belief propagation decoding, BI-AWGN channel, binary additive white Gaussian noise channel, binary erasure channel, BP estimation, Channel Coding, Complexity theory, error rate reduction, error statistics, Expectation, finite-length codes, Iterative decoding, LDPC codes, LDPC decoding, low-density parity-check decoding, Maximum likelihood decoding, parity check codes, posterior distribution, Propagation, TEP algorithm, tree-structured expectation propagation algorithm, trees (mathematics)},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Salamanca2012,

title = {Tree-Structured Expectation Propagation for LDPC Decoding over the AWGN Channel},

author = {Luis Salamanca and Juan Jose Murillo-Fuentes and Pablo M Olmos and Fernando Perez-Cruz},

url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6349716},

issn = {1551-2541},

year  = {2012},

date = {2012-01-01},

booktitle = {2012 IEEE International Workshop on Machine Learning for Signal Processing},

pages = {1--6},

publisher = {IEEE},

address = {Santander},

abstract = {In this paper, we propose the tree-structured expectation propagation (TEP) algorithm for low-density parity-check (LDPC) decoding over the additive white Gaussian noise (AWGN) channel. By imposing a tree-like approximation over the graphical model of the code, this algorithm introduces pairwise marginal constraints over pairs of variables, which provide joint information of the variables related. Thanks to this, the proposed TEP decoder improves the performance of the standard belief propagation (BP) solution. An efficient way of constructing the tree-like structure is also described. The simulation results illustrate the TEP decoder gain in the finite-length regime, compared to the standard BP solution. For code lengths shorter than n = 512, the gain in the waterfall region achieves up to 0.25 dB. We also notice a remarkable reduction of the error floor.},

keywords = {additive white Gaussian noise channel, Approximation algorithms, Approximation methods, approximation theory, AWGN channel, AWGN channels, belief propagation solution, Bit error rate, Decoding, error floor reduction, finite-length regime, Gain, Joints, LDPC decoding, low-density parity-check decoding, pairwise marginal constraint, parity check codes, TEP decoder, tree-like approximation, tree-structured expectation propagation, trees (mathematics)},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Olmos2012,

title = {Finite-Length Performance of Spatially-Coupled LDPC Codes under TEP Decoding},

author = {Pablo M Olmos and Fernando Perez-Cruz and Luis Salamanca and Juan Jose Murillo-Fuentes},

url = {http://ieeexplore.ieee.org/articleDetails.jsp?arnumber=6404722},

isbn = {978-1-4673-0223-4},

year  = {2012},

date = {2012-01-01},

booktitle = {2012 IEEE Information Theory Workshop},

pages = {1--6},

publisher = {IEEE},

address = {Lausanne},

keywords = {asymptotic limit, belief propagation decoding, Complexity theory, convolutional codes, convolutional LDPC codes, Decoding, decoding latency, decoding threshold, erasure channel, Error analysis, error rates, finite-length analysis, finite-length performance, maximum a posteriori threshold, maximum likelihood estimation, parity check codes, regular sparse codes, spatially-coupled LDPC codes, TEP decoding, tree-structured expectation propagation, underlying regular code, very large code length, window-sliding scheme},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Olmos2012a,

title = {Finite-Length Analysis of the TEP Decoder for LDPC Ensembles over the BEC},

author = {Pablo M Olmos and Fernando Perez-Cruz and Luis Salamanca and Juan Jose Murillo-Fuentes},

url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6283932},

issn = {2157-8095},

year  = {2012},

date = {2012-01-01},

booktitle = {2012 IEEE International Symposium on Information Theory Proceedings},

pages = {2346--2350},

publisher = {IEEE},

address = {Cambridge, MA},

abstract = {In this work, we analyze the finite-length performance of low-density parity check (LDPC) ensembles decoded over the binary erasure channel (BEC) using the tree-expectation propagation (TEP) algorithm. In a previous paper, we showed that the TEP improves the BP performance for decoding regular and irregular short LDPC codes, but the perspective was mainly empirical. In this work, given the degree-distribution of an LDPC ensemble, we explain and predict the range of code lengths for which the TEP improves the BP solution. In addition, for LDPC ensembles that present a single critical point, we propose a scaling law to accurately predict the performance in the waterfall region. These results are of critical importance to design practical LDPC codes for the TEP decoder.},

keywords = {Approximation methods, BEC, binary codes, binary erasure channel, Decoding, Error analysis, error probability, finite-length analysis, LDPC ensembles, low-density parity check ensembles, parity check codes, TEP decoder, Trajectory, tree-expectation propagation algorithm, waterfall region},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Olmos2011,

title = {Scaling Behavior of Convolutional LDPC Ensembles over the BEC},

author = {Pablo M Olmos and Rudiger Urbanke},

url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6033863},

issn = {2157-8095},

year  = {2011},

date = {2011-01-01},

booktitle = {2011 IEEE International Symposium on Information Theory Proceedings},

pages = {1816--1820},

publisher = {IEEE},

address = {Saint Petersburg},

abstract = {We study the scaling behavior of coupled sparse graph codes over the binary erasure channel. In particular, let 2L+1 be the length of the coupled chain, let M be the number of variables in each of the 2L+1 local copies, let ℓ be the number of iterations, let Pb denote the bit error probability, and let ∈ denote the channel parameter. We are interested in how these quantities scale when we let the blocklength (2L + 1)M tend to infinity. Based on empirical evidence we show that the threshold saturation phenomenon is rather stable with respect to the scaling of the various parameters and we formulate some general rules of thumb which can serve as a guide for the design of coding systems based on coupled graphs.},

keywords = {BEC, binary codes, binary erasure channel, Bit error rate, convolutional codes, convolutional LDPC ensembles, coupled sparse graph codes, Couplings, Decoding, error probability, Iterative decoding, parity check codes, scaling behavior},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Olmos2011b,

title = {Capacity Achieving LDPC Ensembles for the TEP Decoder in Erasure Channels},

author = {Pablo M Olmos and Juan Jose Murillo-Fuentes and Fernando Perez-Cruz},

url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6033993},

issn = {2157-8095},

year  = {2011},

date = {2011-01-01},

booktitle = {2011 IEEE International Symposium on Information Theory Proceedings},

pages = {2398--2402},

publisher = {IEEE},

address = {St. Petersburg},

abstract = {In this work we address the design of degree distributions (DD) of low-density parity-check (LDPC) codes for the tree-expectation propagation (TEP) decoder. The optimization problem to find distributions to maximize the TEP decoding threshold for a fixed-rate code can not be analytically solved. We derive a simplified optimization problem that can be easily solved since it is based in the analytic expressions of the peeling decoder. Two kinds of solutions are obtained from this problem: we either design LDPC ensembles for which the BP threshold equals the MAP threshold or we get LDPC ensembles for which the TEP threshold outperforms the BP threshold, even achieving the MAP capacity in some cases. Hence, we proved that there exist ensembles for which the MAP solution can be obtained with linear complexity even though the BP threshold does not achieve the MAP threshold.},

keywords = {BP threshold, Complexity theory, Decoding, Differential equations, erasure channels, fixed-rate code, Iterative decoding, LDPC, low-density parity-check codes, MAP capacity, MAP threshold, optimisation, Optimization, optimization problem, parity check codes, TEP decoder, tree-expectation propagation decoder},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Salamanca2011a,

title = {MAP Decoding for LDPC Codes over the Binary Erasure Channel},

author = {Luis Salamanca and Pablo M Olmos and Juan Jose Murillo-Fuentes and Fernando Perez-Cruz},

url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6089364},

isbn = {978-1-4577-0437-6},

year  = {2011},

date = {2011-01-01},

booktitle = {2011 IEEE Information Theory Workshop},

pages = {145--149},

publisher = {IEEE},

address = {Paraty},

abstract = {In this paper, we propose a decoding algorithm for LDPC codes that achieves the MAP solution over the BEC. This algorithm, denoted as generalized tree-structured expectation propagation (GTEP), extends the idea of our previous work, the TEP decoder. The GTEP modifies the graph by eliminating a check node of any degree and merging this information with the remaining graph. The GTEP decoder upon completion either provides the unique MAP solution or a tree graph in which the number of parent nodes indicates the multiplicity of the MAP solution. This algorithm can be easily described for the BEC, and it can be cast as a generalized peeling decoder. The GTEP naturally optimizes the complexity of the decoder, by looking for checks nodes of minimum degree to be eliminated first.},

keywords = {binary erasure channel, Channel Coding, computational complexity, Decoding, generalized peeling decoder, generalized tree-structured expectation propagatio, graphical models, Iterative decoding, LDPC codes, MAP decoding, MAP decoding algorithm, Maximum likelihood decoding, parity check codes, TEP decoder, tree graph theory, Tree graphs, tree-structured expectation propagation, trees (mathematics)},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Olmos2010,

title = {Tree-Structure Expectation Propagation for Decoding LDPC Codes over Binary Erasure Channels},

author = {Pablo M Olmos and Juan Jose Murillo-Fuentes and Fernando Perez-Cruz},

url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5513636},

isbn = {978-1-4244-7892-7},

year  = {2010},

date = {2010-01-01},

booktitle = {2010 IEEE International Symposium on Information Theory},

pages = {799--803},

publisher = {IEEE},

address = {Austin, TX},

abstract = {Expectation Propagation is a generalization to Belief Propagation (BP) in two ways. First, it can be used with any exponential family distribution over the cliques in the graph. Second, it can impose additional constraints on the marginal distributions. We use this second property to impose pair-wise marginal distribution constraints in some check nodes of the LDPC Tanner graph. These additional constraints allow decoding the received codeword when the BP decoder gets stuck. In this paper, we first present the new decoding algorithm, whose complexity is identical to the BP decoder, and we then prove that it is able to decode codewords with a larger fraction of erasures, as the block size tends to infinity. The proposed algorithm can be also understood as a simplification of the Maxwell decoder, but without its computational complexity. We also illustrate that the new algorithm outperforms the BP decoder for finite block-size codes.},

keywords = {belief propagation, binary erasure channels, Bipartite graph, BP decoder, Capacity planning, Channel Coding, codeword, computational complexity, Decoding, Finishing, graph theory, H infinity control, LDPC code decoding, LDPC Tanner graph, Maxwell decoder, parity check codes, Performance analysis, tree structure expectation propagation, trees (mathematics), Upper bound},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Salamanca2010a,

title = {Channel Decoding with a Bayesian Equalizer},

author = {Luis Salamanca and Juan Jose Murillo-Fuentes and Fernando Perez-Cruz},

url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5513348},

isbn = {978-1-4244-7892-7},

year  = {2010},

date = {2010-01-01},

booktitle = {2010 IEEE International Symposium on Information Theory},

pages = {1998--2002},

publisher = {IEEE},

address = {Austin, TX},

abstract = {Low-density parity-check (LPDC) decoders assume the channel estate information (CSI) is known and they have the true a posteriori probability (APP) for each transmitted bit. But in most cases of interest, the CSI needs to be estimated with the help of a short training sequence and the LDPC decoder has to decode the received word using faulty APP estimates. In this paper, we study the uncertainty in the CSI estimate and how it affects the bit error rate (BER) output by the LDPC decoder. To improve these APP estimates, we propose a Bayesian equalizer that takes into consideration not only the uncertainty due to the noise in the channel, but also the uncertainty in the CSI estimate, reducing the BER after the LDPC decoder.},

keywords = {a posteriori probability, Bayesian equalizer, Bayesian methods, BER, Bit error rate, Channel Coding, channel decoding, channel estate information, Communication channels, Decoding, equalisers, Equalizers, error statistics, low-density parity-check decoders, LPDC decoders, Maximum likelihood decoding, maximum likelihood detection, maximum likelihood estimation, Noise reduction, parity check codes, Probability, Uncertainty},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Fresia2009,

title = {Optimized Concatenated LDPC Codes for Joint Source-Channel Coding},

author = {Maria Fresia and Fernando Perez-Cruz and Vincent H Poor},

url = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5205766},

isbn = {978-1-4244-4312-3},

year  = {2009},

date = {2009-01-01},

booktitle = {2009 IEEE International Symposium on Information Theory},

pages = {2131--2135},

publisher = {IEEE},

address = {Seoul},

abstract = {In this paper a scheme for joint source-channel coding based on low-density-parity-check (LDPC) codes is investigated. Two concatenated independent LDPC codes are used in the transmitter: one for source coding and the other for channel coding, with a joint belief propagation decoder. The asymptotic behavior is analyzed using EXtrinsic Information Transfer (EXIT) charts and this approximation is corroborated with illustrative experiments. The optimization of the degree distributions for our sparse code to maximize the information transmission rate is also considered.},

keywords = {approximation theory, asymptotic behavior analysis, Channel Coding, combined source-channel coding, Concatenated codes, Decoding, Entropy, EXIT chart, extrinsic information transfer, H infinity control, Information analysis, joint belief propagation decoder, joint source-channel coding, low-density-parity-check code, optimized concatenated independent LDPC codes, parity check codes, Redundancy, source coding, transmitter, Transmitters},

pubstate = {published},

tppubtype = {inproceedings}

}