Analysis of sum-product decoding of low-density parity-check codes using a Gaussian approximation

By Sae-Young Chung, T. Richardson, Rüdiger L. Urbanke. IEEE Transactions on Information Theory, 2001

1,233 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/08c23fd7c0e96cb50b0fabe3c2203be4b188d465

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

In Electrical and Electronic Engineering

Citations in the corpus

Performance analysis and code optimization of low density parity-check codes on Rayleigh fading channels (2001, neutral): “Refer to [6] for details.”
Sparse Solution Of Underdetermined Linear Equations By Stagewise Orthogonal Matching Pursuit (2006, methodology): “Finally the specific analysis technique we have developed ‐ the conditioned Gaussian limit ‐ bears some resemblance to density evolution schemes used in the MUD/CDMA literature, eg [4, 6, 13 , 30].”
LDPC block and convolutional codes based on circulant matrices (2004, methodology): “We also note that the thresholds of the irregular codes, described here, calculated using the technique described in [16] , are superior to those of the regular codes of the original construction.”
Sparse Solution of Underdetermined Systems of Linear Equations by Stagewise Orthogonal Matching Pursuit (2012, methodology): “, onion-peeling schemes [10] or iterative decoders [4], [6], [13]—is completely consistent with our approach in this paper: stagewise least-squares projection when the nonzeros in have a power-law distribution is something like onion-peeling; minimization is something like a Bayesian maximum a poste”
The exit chart - introduction to extrinsic information transfer in iterative processing (2004, background): “process is the density evolution described in [8] and [ 9 ].”
Turbo equalization: principles and new results (2002, methodology): “The algorithms for the approximate MMSE LE’s (I) and (II) can be implemented in the frequency domain [30], which further decreases the computational load for specific systems.”
Iterative Channel Estimation Using LSE and Sparse Message Passing for MmWave MIMO Systems (2016, methodology): “parity check code, in which the output message called extrinsic information on each edge is calculated by the messages on the other edges that are connected with the same node [15], [41], [42], [43], [44]. 2) Message Update at Sum Nodes : To analyze a sum node that is shown in the Fig. 4, we can obt”
Compression of binary sources with side information at the decoder using LDPC codes (2002, methodology): “Much better results are expected from LDPC codes with improved irregular code design [9], [11]–[13].”
Efficient Design and Decoding of Polar Codes (2012, background): “It was s uggested in [13] to approximate the distributions of intermed iate”
Rate-compatible puncturing of low-density parity-check codes (2004, methodology): “For and , and are defined in [ 10 ] as and (6) is equivalently expressed as”
Iterative multiuser joint decoding: unified framework and asymptotic analysis (2001, neutral): “As in (51), we make a Gaussian approximation of the SISO decoder output and let [32], [33]”
Rate-adaptive codes for distributed source coding (2006, background): “Thus, the global degree distribution can be used to tune the performance of the codes [26].”
Raptor codes on binary memoryless symmetric channels (2006, methodology): “Then, we will show in Section V that the method of Gaussian approximation [17], [18] can be adapted to the case of Raptor codes.”
Design of regular (2,d/sub c/)-LDPC codes over GF(q) using their binary images (2008, methodology): “Some efficient optimization methods of the code profile and the matrix structure have been derived for both long [22][3] and moderate [13] length cases.”
Generalized approximate message passing for estimation with random linear mixing (2010, methodology): “Gaussian approximations are also used in expectation propagation [32], [33], as well as the analysis and design of LDPC codes [34]–[36].”
Iterative turbo decoder analysis based on density evolution (2000, methodology): “The SNR characteristic for the collection of degree-dc check nodes is obtained by averaging a product of tanh functions, as shown in [9].”