2,029 research outputs found
Iterative Bounded Distance Decoding of Product Codes with Scaled Reliability
We propose a modified iterative bounded distance decoding of product codes.
The proposed algorithm is based on exchanging hard messages iteratively and
exploiting channel reliabilities to make hard decisions at each iteration.
Performance improvements up to 0.26 dB are achieved
Iterative Bounded Distance Decoding of Product Codes with Scaled Reliability
We propose a modified iterative bounded distance decoding of product codes. The proposed algorithm is based on exchanging hard messages iteratively and exploiting channel reliabilities to make hard decisions at each iteration. Performance improvements up to 0.26 dB are achieved
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
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 0.29 dB and 0.31 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
Binary Message Passing Decoding of Product Codes Based on Generalized Minimum Distance Decoding
We propose a binary message passing decoding algorithm for product codes
based on generalized minimum distance decoding (GMDD) of the component codes,
where the last stage of the GMDD makes a decision based on the Hamming distance
metric. The proposed algorithm closes half of the gap between conventional
iterative bounded distance decoding (iBDD) and turbo product decoding based on
the Chase--Pyndiah algorithm, at the expense of some increase in complexity.
Furthermore, the proposed algorithm entails only a limited increase in data
flow compared to iBDD.Comment: Invited paper to the 53rd Annual Conference on Information Sciences
and Systems (CISS), Baltimore, MD, March 2019. arXiv admin note: text overlap
with arXiv:1806.1090
Energy-Efficient Soft-Assisted Product Decoders
We implement a 1-Tb/s 0.63-pJ/bit soft-assisted product decoder in a 28-nm
technology. The decoder uses one bit of soft information to improve its net
coding gain by 0.2 dB, reaching 10.3-10.4 dB, which is similar to that of more
complex hard-decision staircase decoders
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
Binary Message Passing Decoding of Product Codes Based on Generalized Minimum Distance Decoding: (Invited Paper)
We propose a binary message passing decoding algorithm for product codes based on generalized minimum distance decoding (GMDD) of the component codes, where the last stage of the GMDD makes a decision based on the Hamming distance metric. The proposed algorithm closes half of the gap between conventional iterative bounded distance decoding (iBDD) and turbo product decoding based on the Chase–Pyndiah algorithm at a bit error rate of , at the expense of some increase in complexity. The proposed algorithm entails only a limited increase in data flow compared to iBDD
Improved Soft-Aided Decoding of Product Codes With Dynamic Reliability Scores
Products codes (PCs) are conventionally decoded with efficient iterative bounded-distance decoding (iBDD) based on hard-decision channel outputs which entails a performance loss compared to a soft-decision decoder. Recently, several hybrid algorithms have been proposed aimed to improve the performance of iBDD decoders via the aid of a certain amount of soft information while keeping the decoding complexity similarly low as in iBDD. We propose a novel hybrid low-complexity decoder for PCs based on error-and-erasure (EaE) decoding and dynamic reliability scores (DRSs). This decoder is based on a novel EaE component code decoder, which is able to decode beyond the designed distance of the component code but suffers from an increased miscorrection probability. The DRSs, reflecting the reliability of a codeword bit, are used to detect and avoid miscorrections. Simulation results show that this policy can reduce the miscorrection rate significantly and improves the decoding performance. The decoder requires only ternary message passing and a slight increase of computational complexity compared to iBDD, which makes it suitable for high-speed communication systems. Coding gains of up to 1.2 dB compared to the conventional iBDD decoder are observed
Improved Soft-aided Decoding of Product Codes with Dynamic Reliability Scores
Products codes (PCs) are conventionally decoded with efficient iterative
bounded-distance decoding (iBDD) based on hard-decision channel outputs which
entails a performance loss compared to a soft-decision decoder. Recently,
several hybrid algorithms have been proposed aimed to improve the performance
of iBDD decoders via the aid of a certain amount of soft information while
keeping the decoding complexity similarly low as in iBDD. We propose a novel
hybrid low-complexity decoder for PCs based on error-and-erasure (EaE) decoding
and dynamic reliability scores (DRSs). This decoder is based on a novel EaE
component code decoder, which is able to decode beyond the designed distance of
the component code but suffers from an increased miscorrection probability. The
DRSs, reflecting the reliability of a codeword bit, are used to detect and
avoid miscorrections. Simulation results show that this policy can reduce the
miscorrection rate significantly and improves the decoding performance. The
decoder requires only ternary message passing and a slight increase of
computational complexity compared to iBDD, which makes it suitable for
high-speed communication systems. Coding gains of up to 1.2 dB compared to the
conventional iBDD decoder are observed.Comment: Submitted to IEE
- …