82 research outputs found
Critical Point for Maximum Likelihood Decoding of Linear Block Codes
In this letter, the SNR value at which the error performance curve of a soft
decision maximum likelihood decoder reaches the slope corresponding to the code
minimum distance is determined for a random code. Based on this value, referred
to as the critical point, new insight about soft bounded distance decoding of
random-like codes (and particularly Reed-Solomon codes) is provided.Comment: to appear IEEE Communications Letter
On the Growth Rate of the Weight Distribution of Irregular Doubly-Generalized LDPC Codes
In this paper, an expression for the asymptotic growth rate of the number of
small linear-weight codewords of irregular doubly-generalized LDPC (D-GLDPC)
codes is derived. The expression is compact and generalizes existing results
for LDPC and generalized LDPC (GLDPC) codes. Assuming that there exist check
and variable nodes with minimum distance 2, it is shown that the growth rate
depends only on these nodes. An important connection between this new result
and the stability condition of D-GLDPC codes over the BEC is highlighted. Such
a connection, previously observed for LDPC and GLDPC codes, is now extended to
the case of D-GLDPC codes.Comment: 10 pages, 1 figure, presented at the 46th Annual Allerton Conference
on Communication, Control and Computing (this version includes additional
appendix
Trellises and Trellis-Based Decoding Algorithms for Linear Block Codes
In a coded communication system with equiprobable signaling, MLD minimizes the word error probability and delivers the most likely codeword associated with the corresponding received sequence. This decoding has two drawbacks. First, minimization of the word error probability is not equivalent to minimization of the bit error probability. Therefore, MLD becomes suboptimum with respect to the bit error probability. Second, MLD delivers a hard-decision estimate of the received sequence, so that information is lost between the input and output of the ML decoder. This information is important in coded schemes where the decoded sequence is further processed, such as concatenated coding schemes, multi-stage and iterative decoding schemes. In this chapter, we first present a decoding algorithm which both minimizes bit error probability, and provides the corresponding soft information at the output of the decoder. This algorithm is referred to as the MAP (maximum aposteriori probability) decoding algorithm
Trellises and Trellis-Based Decoding Algorithms for Linear Block Codes
For long linear block codes, maximum likelihood decoding based on full code trellises would be very hard to implement if not impossible. In this case, we may wish to trade error performance for the reduction in decoding complexity. Sub-optimum soft-decision decoding of a linear block code based on a low-weight sub-trellis can be devised to provide an effective trade-off between error performance and decoding complexity. This chapter presents such a suboptimal decoding algorithm for linear block codes. This decoding algorithm is iterative in nature and based on an optimality test. It has the following important features: (1) a simple method to generate a sequence of candidate code-words, one at a time, for test; (2) a sufficient condition for testing a candidate code-word for optimality; and (3) a low-weight sub-trellis search for finding the most likely (ML) code-word
Spectral Shape of Check-Hybrid GLDPC Codes
This paper analyzes the asymptotic exponent of both the weight spectrum and
the stopping set size spectrum for a class of generalized low-density
parity-check (GLDPC) codes. Specifically, all variable nodes (VNs) are assumed
to have the same degree (regular VN set), while the check node (CN) set is
assumed to be composed of a mixture of different linear block codes (hybrid CN
set). A simple expression for the exponent (which is also referred to as the
growth rate or the spectral shape) is developed. This expression is consistent
with previous results, including the case where the normalized weight or
stopping set size tends to zero. Furthermore, it is shown how certain symmetry
properties of the local weight distribution at the CNs induce a symmetry in the
overall weight spectral shape function.Comment: 6 pages, 3 figures. Presented at the IEEE ICC 2010, Cape Town, South
Africa. A minor typo in equation (9) has been correcte
Growth Rate of the Weight Distribution of Doubly-Generalized LDPC Codes: General Case and Efficient Evaluation
The growth rate of the weight distribution of irregular doubly-generalized
LDPC (D-GLDPC) codes is developed and in the process, a new efficient numerical
technique for its evaluation is presented. The solution involves simultaneous
solution of a 4 x 4 system of polynomial equations. This represents the first
efficient numerical technique for exact evaluation of the growth rate, even for
LDPC codes. The technique is applied to two example D-GLDPC code ensembles.Comment: 6 pages, 1 figure. Proc. IEEE Globecom 2009, Hawaii, USA, November 30
- December 4, 200
Stability of Iterative Decoding of Multi-Edge Type Doubly-Generalized LDPC Codes Over the BEC
Using the EXIT chart approach, a necessary and sufficient condition is
developed for the local stability of iterative decoding of multi-edge type
(MET) doubly-generalized low-density parity-check (D-GLDPC) code ensembles. In
such code ensembles, the use of arbitrary linear block codes as component codes
is combined with the further design of local Tanner graph connectivity through
the use of multiple edge types. The stability condition for these code
ensembles is shown to be succinctly described in terms of the value of the
spectral radius of an appropriately defined polynomial matrix.Comment: 6 pages, 3 figures. Presented at Globecom 2011, Houston, T
Doubly-Generalized LDPC Codes: Stability Bound over the BEC
The iterative decoding threshold of low-density parity-check (LDPC) codes
over the binary erasure channel (BEC) fulfills an upper bound depending only on
the variable and check nodes with minimum distance 2. This bound is a
consequence of the stability condition, and is here referred to as stability
bound. In this paper, a stability bound over the BEC is developed for
doubly-generalized LDPC codes, where the variable and the check nodes can be
generic linear block codes, assuming maximum a posteriori erasure correction at
each node. It is proved that in this generalized context as well the bound
depends only on the variable and check component codes with minimum distance 2.
A condition is also developed, namely the derivative matching condition, under
which the bound is achieved with equality.Comment: Submitted to IEEE Trans. on Inform. Theor
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