On the design of low-density parity-check codes within 0.0045 dB of the Shannon limit

By Sae-Young Chung, G. David Forney Jr., T. Richardson, Rüdiger L. Urbanke. IEEE Communications Letters, 2001

1,666 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/c9257d782ba57d62e0ec4a1200527a4cc0ed2855

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

End-to-End Energy Modeling and Analysis of Long-Haul Coherent Transmission Systems (2014, background): “Low density parity check (LDPC) codes can achieve performance approaching information-theoretic limits [10], [11].”
Probabilistic Constellation Shaping for Optical Fiber Communications (2019, methodology): “04 dB at BER = 10−6 using belief-propagation decoding with up to 2000 decoding iterations [64].”
Iterative Decoding Threshold Analysis for LDPC Convolutional Codes (2010, neutral): “We now present the thresholds of terminated LDPCC codes for a binary input AWGN channel, computed by discretized density evolution [30].”
Design of efficiently encodable moderate-length high-rate irregular LDPC codes (2004, methodology): “A code design algorithm based on the combination of density evolution and differential evolution optimization with a modified cost function is presented.”
Distributed source coding for sensor networks (2004, background): “algorithm [23]2. LDPC codes are the most powerful channel codes nowadays [ 25 ] and they can be”
The art of error correcting coding (2002, background): “0045 dB away from the Shannon limit for binary transmission over an AWGN channel (Chung et al. 2001).”
A 220 mW 1 Gb/s 1024-bit rate-1/2 low density parity check code decoder (2001, background): “The most powerful codes currently known are 1 million bit and 10 million bit, rate-1/2, LDPC codes, achieving a capacity which is only 0.13 dB and 0.04 dB, respectively, from the Shannon limit for a bit error rate (BER) probability of 10 [7], [8].”
Polar Codes for Channel and Source Coding (2009, background): “0045dB [31] were constructed.”
Regular and irregular progressive edge-growth tanner graphs (2005, methodology): “Although random graphs have been used to construct LDPC codes with impressive performance [16], [20], large girths facilitate iterative decoding and impose a respectable minimum distance bound that enhances decoding performance in a high-signal-to-noise (SNR) regime.”
Spectral efficiency limits and modulation/detection techniques for DWDM systems (2004, background): “…Efficiency Limits and Modulation/Detection Techniques for DWDM Systems Joseph M. Kahn, Fellow, IEEE, and Keang-Po Ho, Senior Member, IEEE Invited Paper Abstract—Information-theoretic limits to spectral efficiency…”
LDPC block and convolutional codes based on circulant matrices (2004, background): “For example, in [1], Chung et al. presented a block length (ten million bits) rate- LDPC code that achieves reliable performance—a bit error rate (BER)—on an additive white Gaussian noise (AWGN) channel with a signal-to-noise ratio (SNR) within 0.04 dB of the Shannon limit.”
Decoding Algorithms for Nonbinary LDPC Codes Over GF$(q)$ (2007, background): “very long code lengths [1], [2], [4], [5].”
Iterative turbo decoder analysis based on density evolution (2000, methodology): “Our methods in this article are similar to all of these approaches, and also to analysis of the turbo decoder algorithm by Agrawal and Vardy [25] and of turbo decoder thresholds by Richardson and Urbanke [26], Vialle and Boutros [27], and Chung and Forney [28].”
Progressive edge-growth Tanner graphs (2001, methodology): “Although random graphs have been used to construct LDPC codes with impressive performance [5, 9], there is no guarantee that any given random graph also defines a good code with a suitable shortest cycle (girth) to facilitate iterative decoding,”
Rateless codes on noisy channels (2004, background): “In this paper, we focus on the BSC and the AWGNC, but we hope to extend our studies to time varying and fading channels.”
PRISM: A Video Coding Paradigm With Motion Estimation at the Decoder (2007, background): “codes [37], [42] and LDPC codes [36], [43] need to be”