18,345 research outputs found
Coding for Parallel Channels: Gallager Bounds for Binary Linear Codes with Applications to Repeat-Accumulate Codes and Variations
This paper is focused on the performance analysis of binary linear block
codes (or ensembles) whose transmission takes place over independent and
memoryless parallel channels. New upper bounds on the maximum-likelihood (ML)
decoding error probability are derived. These bounds are applied to various
ensembles of turbo-like codes, focusing especially on repeat-accumulate codes
and their recent variations which possess low encoding and decoding complexity
and exhibit remarkable performance under iterative decoding. The framework of
the second version of the Duman and Salehi (DS2) bounds is generalized to the
case of parallel channels, along with the derivation of their optimized tilting
measures. The connection between the generalized DS2 and the 1961 Gallager
bounds, addressed by Divsalar and by Sason and Shamai for a single channel, is
explored in the case of an arbitrary number of independent parallel channels.
The generalization of the DS2 bound for parallel channels enables to re-derive
specific bounds which were originally derived by Liu et al. as special cases of
the Gallager bound. In the asymptotic case where we let the block length tend
to infinity, the new bounds are used to obtain improved inner bounds on the
attainable channel regions under ML decoding. The tightness of the new bounds
for independent parallel channels is exemplified for structured ensembles of
turbo-like codes. The improved bounds with their optimized tilting measures
show, irrespectively of the block length of the codes, an improvement over the
union bound and other previously reported bounds for independent parallel
channels; this improvement is especially pronounced for moderate to large block
lengths.Comment: Submitted to IEEE Trans. on Information Theory, June 2006 (57 pages,
9 figures
Low-Density Graph Codes for slow fading Relay Channels
We study Low-Density Parity-Check (LDPC) codes with iterative decoding on
block-fading (BF) Relay Channels. We consider two users that employ coded
cooperation, a variant of decode-and-forward with a smaller outage probability
than the latter. An outage probability analysis for discrete constellations
shows that full diversity can be achieved only when the coding rate does not
exceed a maximum value that depends on the level of cooperation. We derive a
new code structure by extending the previously published full-diversity
root-LDPC code, designed for the BF point-to-point channel, to exhibit a
rate-compatibility property which is necessary for coded cooperation. We
estimate the asymptotic performance through a new density evolution analysis
and the word error rate performance is determined for finite length codes. We
show that our code construction exhibits near-outage limit performance for all
block lengths and for a range of coding rates up to 0.5, which is the highest
possible coding rate for two cooperating users.Comment: Accepted for publication in IEEE Transactions on Information Theor
Low-Density Parity-Check Codes for Nonergodic Block-Fading Channels
We solve the problem of designing powerful low-density parity-check (LDPC)
codes with iterative decoding for the block-fading channel. We first study the
case of maximum-likelihood decoding, and show that the design criterion is
rather straightforward. Unfortunately, optimal constructions for
maximum-likelihood decoding do not perform well under iterative decoding. To
overcome this limitation, we then introduce a new family of full-diversity LDPC
codes that exhibit near-outage-limit performance under iterative decoding for
all block-lengths. This family competes with multiplexed parallel turbo codes
suitable for nonergodic channels and recently reported in the literature.Comment: Submitted to the IEEE Transactions on Information Theor
Binary Message Passing Decoding of Product-like Codes
We propose a novel binary message passing decoding algorithm for product-like
codes based on bounded distance decoding (BDD) of the component codes. The
algorithm, dubbed iterative BDD with scaled reliability (iBDD-SR), exploits the
channel reliabilities and is therefore soft in nature. However, the messages
exchanged by the component decoders are binary (hard) messages, which
significantly reduces the decoder data flow. The exchanged binary messages are
obtained by combining the channel reliability with the BDD decoder output
reliabilities, properly conveyed by a scaling factor applied to the BDD
decisions. We perform a density evolution analysis for generalized low-density
parity-check (GLDPC) code ensembles and spatially coupled GLDPC code ensembles,
from which the scaling factors of the iBDD-SR for product and staircase codes,
respectively, can be obtained. For the white additive Gaussian noise channel,
we show performance gains up to dB and dB for product and
staircase codes compared to conventional iterative BDD (iBDD) with the same
decoder data flow. Furthermore, we show that iBDD-SR approaches the performance
of ideal iBDD that prevents miscorrections.Comment: Accepted for publication in the IEEE Transactions on Communication
Iterative Decoding and Turbo Equalization: The Z-Crease Phenomenon
Iterative probabilistic inference, popularly dubbed the soft-iterative
paradigm, has found great use in a wide range of communication applications,
including turbo decoding and turbo equalization. The classic approach of
analyzing the iterative approach inevitably use the statistical and
information-theoretical tools that bear ensemble-average flavors. This paper
consider the per-block error rate performance, and analyzes it using nonlinear
dynamical theory. By modeling the iterative processor as a nonlinear dynamical
system, we report a universal "Z-crease phenomenon:" the zig-zag or up-and-down
fluctuation -- rather than the monotonic decrease -- of the per-block errors,
as the number of iteration increases. Using the turbo decoder as an example, we
also report several interesting motion phenomenons which were not previously
reported, and which appear to correspond well with the notion of "pseudo
codewords" and "stopping/trapping sets." We further propose a heuristic
stopping criterion to control Z-crease and identify the best iteration. Our
stopping criterion is most useful for controlling the worst-case per-block
errors, and helps to significantly reduce the average-iteration numbers.Comment: 6 page
- …