1,533 research outputs found
Decoding of MDP Convolutional Codes over the Erasure Channel
This paper studies the decoding capabilities of maximum distance profile
(MDP) convolutional codes over the erasure channel and compares them with the
decoding capabilities of MDS block codes over the same channel. The erasure
channel involving large alphabets is an important practical channel model when
studying packet transmissions over a network, e.g, the Internet
Windowed Decoding of Protograph-based LDPC Convolutional Codes over Erasure Channels
We consider a windowed decoding scheme for LDPC convolutional codes that is
based on the belief-propagation (BP) algorithm. We discuss the advantages of
this decoding scheme and identify certain characteristics of LDPC convolutional
code ensembles that exhibit good performance with the windowed decoder. We will
consider the performance of these ensembles and codes over erasure channels
with and without memory. We show that the structure of LDPC convolutional code
ensembles is suitable to obtain performance close to the theoretical limits
over the memoryless erasure channel, both for the BP decoder and windowed
decoding. However, the same structure imposes limitations on the performance
over erasure channels with memory.Comment: 18 pages, 9 figures, accepted for publication in the IEEE
Transactions on Information Theor
Decoding of Convolutional Codes over the Erasure Channel
In this paper we study the decoding capabilities of convolutional codes over
the erasure channel. Of special interest will be maximum distance profile (MDP)
convolutional codes. These are codes which have a maximum possible column
distance increase. We show how this strong minimum distance condition of MDP
convolutional codes help us to solve error situations that maximum distance
separable (MDS) block codes fail to solve. Towards this goal, we define two
subclasses of MDP codes: reverse-MDP convolutional codes and complete-MDP
convolutional codes. Reverse-MDP codes have the capability to recover a maximum
number of erasures using an algorithm which runs backward in time. Complete-MDP
convolutional codes are both MDP and reverse-MDP codes. They are capable to
recover the state of the decoder under the mildest condition. We show that
complete-MDP convolutional codes perform in certain sense better than MDS block
codes of the same rate over the erasure channel.Comment: 18 pages, 3 figures, to appear on IEEE Transactions on Information
Theor
Burst Erasure Correction of 2D convolutional codes
In this paper we address the problem of decoding 2D convolutional codes over the erasure channel. In particular, we present a procedure to recover bursts of erasures that are distributed in a diagonal line. To this end we introduce the notion of balls around a burst of erasures which can be considered an analogue of the notion of sliding window in the context of 1D convolutional codes. The main result reduces the decoding problem of 2D convolutional codes to a problem of decoding a set of associated 1D convolutional codes
Complete j-MDP convolutional codes
Maximum distance profile (MDP) convolutional codes have been proven to be
very suitable for transmission over an erasure channel. In addition, the
subclass of complete MDP convolutional codes has the ability to restart
decoding after a burst of erasures. However, there is a lack of constructions
of these codes over fields of small size. In this paper, we introduce the
notion of complete j-MDP convolutional codes, which are a generalization of
complete MDP convolutional codes, and describe their decoding properties. In
particular, we present a decoding algorithm for decoding erasures within a
given time delay T and show that complete T-MDP convolutional codes are optimal
for this algorithm. Moreover, using a computer search with the MAPLE software,
we determine the minimal binary and non-binary field size for the existence of
(2,1,2) complete j-MDP convolutional codes and provide corresponding
constructions. We give a description of all (2,1,2) complete MDP convolutional
codes over the smallest possible fields, namely F_13 and F_16 and we also give
constructions for (2,1,3) complete 4-MDP convolutional codes over F_128
obtained by a randomized computer search.Comment: 2
Optimal Streaming Codes for Channels with Burst and Arbitrary Erasures
This paper considers transmitting a sequence of messages (a streaming source)
over a packet erasure channel. In each time slot, the source constructs a
packet based on the current and the previous messages and transmits the packet,
which may be erased when the packet travels from the source to the destination.
Every source message must be recovered perfectly at the destination subject to
a fixed decoding delay. We assume that the channel loss model introduces either
one burst erasure or multiple arbitrary erasures in any fixed-sized sliding
window. Under this channel loss assumption, we fully characterize the maximum
achievable rate by constructing streaming codes that achieve the optimal rate.
In addition, our construction of optimal streaming codes implies the full
characterization of the maximum achievable rate for convolutional codes with
any given column distance, column span and decoding delay. Numerical results
demonstrate that the optimal streaming codes outperform existing streaming
codes of comparable complexity over some instances of the Gilbert-Elliott
channel and the Fritchman channel.Comment: 36 pages, 3 figures, 2 table
Threshold Saturation for Spatially Coupled Turbo-like Codes over the Binary Erasure Channel
In this paper we prove threshold saturation for spatially coupled turbo codes
(SC-TCs) and braided convolutional codes (BCCs) over the binary erasure
channel. We introduce a compact graph representation for the ensembles of SC-TC
and BCC codes which simplifies their description and the analysis of the
message passing decoding. We demonstrate that by few assumptions in the
ensembles of these codes, it is possible to rewrite their vector recursions in
a form which places these ensembles under the category of scalar admissible
systems. This allows us to define potential functions and prove threshold
saturation using the proof technique introduced by Yedla et al..Comment: 5 pages, 3figure
Spatially-Coupled Random Access on Graphs
In this paper we investigate the effect of spatial coupling applied to the
recently-proposed coded slotted ALOHA (CSA) random access protocol. Thanks to
the bridge between the graphical model describing the iterative interference
cancelation process of CSA over the random access frame and the erasure
recovery process of low-density parity-check (LDPC) codes over the binary
erasure channel (BEC), we propose an access protocol which is inspired by the
convolutional LDPC code construction. The proposed protocol exploits the
terminations of its graphical model to achieve the spatial coupling effect,
attaining performance close to the theoretical limits of CSA. As for the
convolutional LDPC code case, large iterative decoding thresholds are obtained
by simply increasing the density of the graph. We show that the threshold
saturation effect takes place by defining a suitable counterpart of the
maximum-a-posteriori decoding threshold of spatially-coupled LDPC code
ensembles. In the asymptotic setting, the proposed scheme allows sustaining a
traffic close to 1 [packets/slot].Comment: To be presented at IEEE ISIT 2012, Bosto
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