314 research outputs found
An Iteratively Decodable Tensor Product Code with Application to Data Storage
The error pattern correcting code (EPCC) can be constructed to provide a
syndrome decoding table targeting the dominant error events of an inter-symbol
interference channel at the output of the Viterbi detector. For the size of the
syndrome table to be manageable and the list of possible error events to be
reasonable in size, the codeword length of EPCC needs to be short enough.
However, the rate of such a short length code will be too low for hard drive
applications. To accommodate the required large redundancy, it is possible to
record only a highly compressed function of the parity bits of EPCC's tensor
product with a symbol correcting code. In this paper, we show that the proposed
tensor error-pattern correcting code (T-EPCC) is linear time encodable and also
devise a low-complexity soft iterative decoding algorithm for EPCC's tensor
product with q-ary LDPC (T-EPCC-qLDPC). Simulation results show that
T-EPCC-qLDPC achieves almost similar performance to single-level qLDPC with a
1/2 KB sector at 50% reduction in decoding complexity. Moreover, 1 KB
T-EPCC-qLDPC surpasses the performance of 1/2 KB single-level qLDPC at the same
decoder complexity.Comment: Hakim Alhussien, Jaekyun Moon, "An Iteratively Decodable Tensor
Product Code with Application to Data Storage
Error-correction coding for high-density magnetic recording channels.
Finally, a promising algorithm which combines RS decoding algorithm with LDPC decoding algorithm together is investigated, and a reduced-complexity modification has been proposed, which not only improves the decoding performance largely, but also guarantees a good performance in high signal-to-noise ratio (SNR), in which area an error floor is experienced by LDPC codes.The soft-decision RS decoding algorithms and their performance on magnetic recording channels have been researched, and the algorithm implementation and hardware architecture issues have been discussed. Several novel variations of KV algorithm such as soft Chase algorithm, re-encoded Chase algorithm and forward recursive algorithm have been proposed. And the performance of nested codes using RS and LDPC codes as component codes have been investigated for bursty noise magnetic recording channels.Future high density magnetic recoding channels (MRCs) are subject to more noise contamination and intersymbol interference, which make the error-correction codes (ECCs) become more important. Recent research of replacement of current Reed-Solomon (RS)-coded ECC systems with low-density parity-check (LDPC)-coded ECC systems obtains a lot of research attention due to the large decoding gain for LDPC-coded systems with random noise. In this dissertation, systems aim to maintain the RS-coded system using recent proposed soft-decision RS decoding techniques are investigated and the improved performance is presented
An Optimal Unequal Error Protection LDPC Coded Recording System
For efficient modulation and error control coding, the deliberate flipping
approach imposes the run-length-limited(RLL) constraint by bit error before
recording. From the read side, a high coding rate limits the correcting
capability of RLL bit error. In this paper, we study the low-density
parity-check (LDPC) coding for RLL constrained recording system based on the
Unequal Error Protection (UEP) coding scheme design. The UEP capability of
irregular LDPC codes is used for recovering flipped bits. We provide an
allocation technique to limit the occurrence of flipped bits on the bit with
robust correction capability. In addition, we consider the signal labeling
design to decrease the number of nearest neighbors to enhance the robust bit.
We also apply the density evolution technique to the proposed system for
evaluating the code performances. In addition, we utilize the EXIT
characteristic to reveal the decoding behavior of the recommended code
distribution. Finally, the optimization approach for the best distribution is
proven by differential evolution for the proposed system.Comment: 20 pages, 18 figure
Decoder-in-the-Loop: Genetic Optimization-based LDPC Code Design
LDPC code design tools typically rely on asymptotic code behavior and are
affected by an unavoidable performance degradation due to model imperfections
in the short length regime. We propose an LDPC code design scheme based on an
evolutionary algorithm, the Genetic Algorithm (GenAlg), implementing a
"decoder-in-the-loop" concept. It inherently takes into consideration the
channel, code length and the number of iterations while optimizing the
error-rate of the actual decoder hardware architecture. We construct short
length LDPC codes (i.e., the parity-check matrix) with error-rate performance
comparable to, or even outperforming that of well-designed standardized short
length LDPC codes over both AWGN and Rayleigh fading channels. Our proposed
algorithm can be used to design LDPC codes with special graph structures (e.g.,
accumulator-based codes) to facilitate the encoding step, or to satisfy any
other practical requirement. Moreover, GenAlg can be used to design LDPC codes
with the aim of reducing decoding latency and complexity, leading to coding
gains of up to dB and dB at BLER of for both AWGN and
Rayleigh fading channels, respectively, when compared to state-of-the-art short
LDPC codes. Also, we analyze what can be learned from the resulting codes and,
as such, the GenAlg particularly highlights design paradigms of short length
LDPC codes (e.g., codes with degree-1 variable nodes obtain very good results).Comment: in IEEE Access, 201
Sub-graph based joint sparse graph for sparse code multiple access systems
Sparse code multiple access (SCMA) is a promising air interface candidate technique for next generation mobile networks, especially for massive machine type communications (mMTC). In this paper, we design a LDPC coded SCMA detector by combining the sparse graphs of LDPC and SCMA into one joint sparse graph (JSG). In our proposed scheme, SCMA sparse graph (SSG) defined by small size indicator matrix is utilized to construct the JSG, which is termed as sub-graph based joint sparse graph of SCMA (SG-JSG-SCMA). In this paper, we first study the binary-LDPC (B-LDPC) coded SGJSG- SCMA system. To combine the SCMA variable node (SVN) and LDPC variable node (LVN) into one joint variable node (JVN), a non-binary LDPC (NB-LDPC) coded SG-JSG-SCMA is also proposed. Furthermore, to reduce the complexity of NBLDPC coded SG-JSG-SCMA, a joint trellis representation (JTR) is introduced to represent the search space of NB-LDPC coded SG-JSG-SCMA. Based on JTR, a low complexity joint trellis based detection and decoding (JTDD) algorithm is proposed to reduce the computational complexity of NB-LDPC coded SGJSG- SCMA system. According to the simulation results, SG-JSGSCMA brings significant performance improvement compare to the conventional receiver using the disjoint approach, and it can also outperform a Turbo-structured receiver with comparable complexity. Moreover, the joint approach also has advantages in terms of processing latency compare to the Turbo approaches
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