4,647 research outputs found
Numerical Techniques for Finding the Distances of Quantum Codes
We survey the existing techniques for calculating code distances of classical
codes and apply these techniques to generic quantum codes. For classical and
quantum LDPC codes, we also present a new linked-cluster technique. It reduces
complexity exponent of all existing deterministic techniques designed for codes
with small relative distances (which include all known families of quantum LDPC
codes), and also surpasses the probabilistic technique for sufficiently high
code rates.Comment: 5 pages, 1 figure, to appear in Proceedings of ISIT 2014 - IEEE
International Symposium on Information Theory, Honolul
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
Improved Decoding of Staircase Codes: The Soft-aided Bit-marking (SABM) Algorithm
Staircase codes (SCCs) are typically decoded using iterative bounded-distance
decoding (BDD) and hard decisions. In this paper, a novel decoding algorithm is
proposed, which partially uses soft information from the channel. The proposed
algorithm is based on marking certain number of highly reliable and highly
unreliable bits. These marked bits are used to improve the
miscorrection-detection capability of the SCC decoder and the error-correcting
capability of BDD. For SCCs with -error-correcting
Bose-Chaudhuri-Hocquenghem component codes, our algorithm improves upon
standard SCC decoding by up to ~dB at a bit-error rate (BER) of
. The proposed algorithm is shown to achieve almost half of the gain
achievable by an idealized decoder with this structure. A complexity analysis
based on the number of additional calls to the component BDD decoder shows that
the relative complexity increase is only around at a BER of .
This additional complexity is shown to decrease as the channel quality
improves. Our algorithm is also extended (with minor modifications) to product
codes. The simulation results show that in this case, the algorithm offers
gains of up to ~dB at a BER of .Comment: 10 pages, 12 figure
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
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
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