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Design of Low-Density Parity-Check Codes and Their Decoding Algorithms

조성혜

Published Jan 1, 2018• 0 citations
OpenAlex

Abstract

In this thesis, we propose low-complexity designing algorithms for non-binary low-density parity-check (NB-LDPC) codes over GF(q) with low error floor and low-complexity decoding algorithms for binary LDPC codes. We first propose a low-complexity designing algorithm for for NB-LDPC codes over GF(q) based on message-passing algorithms. Short cycles in an NB-LDPC code may be even more harmful to its performance if they do not satisfy the so-called full rank condition (FRC). This is because they may induce low-weight codewords or absorbing sets in that case. Thus, it is crucial to count the number of short cycles not satisfying the FRC as well as the number of short cycles for analyzing the performance of an NB-LDPC code. In order to count those cycles, we first develop a novel message-passing algorithm and identify how it is related to the FRC.We then propose a low-complexity algorithmfor counting the number of short cycles not satisfying the FRC in an NB-LDPC code, as well as the number of short cycles. The proposed algorithm is not only theoretically validated, but its computational and storage complexities are also computed. It does not require cycle enumeration with high complexity, and therefore is still feasible even in the case of large code length, say ≤ 5000, unlike the conventional methods. Based on it, we also provide a locally optimal rule to choose a nonzero element for a given edge and propose a low-complexity algorithm for designing an NB-LDPC code with low error floor. Furthermore, several design examples are presented to verify the validity of the proposed design algorithm. Secondly, we propose a low-complexity decoding algorithm for binary LDPC codes over the binary symmetric channel (BSC). The min-sum (MS) algorithm is a low-complexity decoding algorithm for binary LDPC codes and has lower computational complexity than the sum-product algorithm (SPA). Since the MS algorithm is an approximation of the SPA, it has performance degradation. Furthermore, reducing the number of bits for representing messages to two in a decoding algorithm for further reducing computational and storage complexities, causes significant performance losses. In order to minimize the performance degradation and computational and storage complexities, we propose a low-complexity decoding algorithm which uses several decoders with two-bit precision for binary LDPC codes over the BSC. The proposed algorithm adaptively changes decoders according to the number of unsatisfied check nodes at each iteration. Compared with the SPA using floating-point operations, the proposed decoding algorithm greatly reduces computational and storage complexities with negligible performance losses. Numerical results show that the proposed decoding algorithm has similar performance to the SPA with floating-point operations over the BSC. In the last part of this thesis, low-complexity decoding algorithms of binary LDPC codes for the core layer at fixed receivers in ATSC 3.0 are proposed. Gallager’s decoding algorithms …

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International Conference on Communication Systems and Network Technologies•Apr 1, 2015•1 citation
In this thesis, we propose low-complexity designing algorithms for non-binary low-density
parity-check (NB-LDPC) codes over GF(q) with low error floor and low-complexity decoding
algorithms for binary LDPC codes.
We first propose a low-complexity designing algorithm for for NB-LDPC codes over GF(q)
based on message-passing algorithms. Short cycles in an NB-LDPC code may be even
more harmful to its performance if they do not satisfy the so-called full rank condition
(FRC). This is because they may induce low-weight codewords or absorbing sets in that
case. Thus, it is crucial to count the number of short cycles not satisfying the FRC as well as
the number of short cycles for analyzing the performance of an NB-LDPC code. In order to
count those cycles, we first develop a novel message-passing algorithm and identify how it
is related to the FRC.We then propose a low-complexity algorithmfor counting the number
of short cycles not satisfying the FRC in an NB-LDPC code, as well as the number of short
cycles. The proposed algorithm is not only theoretically validated, but its computational
and storage complexities are also computed. It does not require cycle enumeration with
high complexity, and therefore is still feasible even in the case of large code length, say
≤ 5000, unlike the conventional methods. Based on it, we also provide a locally optimal
rule to choose a nonzero element for a given edge and propose a low-complexity algorithm
for designing an NB-LDPC code with low error floor. Furthermore, several design examples
are presented to verify the validity of the proposed design algorithm.
Secondly, we propose a low-complexity decoding algorithm for binary LDPC codes over
the binary symmetric channel (BSC). The min-sum (MS) algorithm is a low-complexity decoding
algorithm for binary LDPC codes and has lower computational complexity than the
sum-product algorithm (SPA). Since the MS algorithm is an approximation of the SPA, it
has performance degradation. Furthermore, reducing the number of bits for representing
messages to two in a decoding algorithm for further reducing computational and storage
complexities, causes significant performance losses. In order to minimize the performance
degradation and computational and storage complexities, we propose a low-complexity
decoding algorithm which uses several decoders with two-bit precision for binary LDPC
codes over the BSC. The proposed algorithm adaptively changes decoders according to
the number of unsatisfied check nodes at each iteration. Compared with the SPA using
floating-point operations, the proposed decoding algorithm greatly reduces computational
and storage complexities with negligible performance losses. Numerical results show that
the proposed decoding algorithm has similar performance to the SPA with floating-point
operations over the BSC.
In the last part of this thesis, low-complexity decoding algorithms of binary LDPC codes
for the core layer at fixed receivers in ATSC 3.0 are proposed. Gallager’s decoding algorithms
…
Short cycles in a nonbinary low-density parity-check (NB-LDPC) code may be even more harmful to its performance if they do not satisfy the so-called full rank condition (FRC). This is because they may induce low-weight codewords or absorbing sets in that case. Thus, it is important to count the number of short cycles not satisfying the FRC as well as the number of short cycles for analyzing the performance of an NB-LDPC code. In this paper, we first develop a novel message-passing algorithm and identify how it is related to the FRC. We then propose a low-complexity algorithm for counting the number of short cycles not satisfying the FRC in an NB-LDPC code, as well as the number of short cycles. Finally, we propose a low-complexity algorithm for designing an NB-LDPC code with low error floor. Depending on the modulation scheme, the codes constructed by the proposed design algorithm have similar or slightly worse performance, compared with those constructed via the method by Poulliat et al. However, the proposed design algorithm does not require a cycle enumeration algorithm with high complexity, and therefore is feasible even in the case of large code length, say ≥5000.
Trapping sets with short cycles are known to give a detrimental effect on the error floor performance of a low-density parity-check (LDPC) code. Unlike in binary LDPC codes., short cycles in a nonbinary low-density parity-check (NB-LDPC) code may be even more harmful to its performance if they do not satisfy the so-called full rank condition (FRC). This is because they may induce low-weight codewords or absorbing sets in that case. Thus, it is crucial to count the number of short cycles not satisfying the FRC as well as the number of short cycles for analyzing the performance of an NB-LDPC code. In this paper, we first develop a novel message-passing algorithm and identify how it is related to the FRC. We then propose a low-complexity algorithm for counting the number of short cycles not satisfying the FRC in an NB-LDPC code, as well as the number of short cycles.
In the information theory , the non- binary low density parity check  (NB-LDPC) code is a  linear error correcting code , a method of transmitting message over a  noisy transmission channel. LDPCcodes are  capacity-approaching codes , which  means  that  practical constructions exist  that allow the noise threshold to be set very close to the theoretical maximum for a symmetric memory less channel.Using iterative  belief propagation techniques, NB-LDPC codes can be decoded in time linear to their block length. Non-binary low-density parity-check codes can achieve higher performance than their binary counterparts. Recently, two algorithms were developed for decoding NB-LDPC codes: iterative hard reliability-based majority-logic decoding (IHRB-MLGD) and iterative soft reliability-based majority-logic decoding (ISRB-MLGD has better performance-complexity tradeoffs than previous algorithms. This paper first proposes message-passing in such a way that we can reduce the memory consumption to a greater extent at the same time there should not be performance loss. By using enhanced iterative reliability-based majority-logic decoding algorithms we can achieve effective complexity-performance and noise free design. Compared to previous designs, our proposed decoders have at least tens of times lower complexity with moderate coding gain loss.
This thesis is focused on the design and implementation of binary low-density parity-check (LDPC) code decoders for high-speed modern communication systems. The basic of LDPC codes and the performance and bottlenecks, in terms of complexity and hardware efficiency, of the main soft-decision and hard-decision decoding algorithms (such as Min-Sum, Optimized 2-bit Min-Sum and Reliability-based iterative Majority-Logic) are analyzed. The complexity and performance of those algorithms are improved to allow efficient hardware architectures.\n\nA new decoding algorithm called One-Minimum Min-Sum is proposed. It reduces considerably the complexity of the check node update equations of the Min-Sum algorithm. The second minimum is estimated from the first minimum value by a means of a linear approximation that allows a dynamic adjustment. The Optimized 2-bit Min-Sum algorithm is modified to initialize it with the complete LLR values and to introduce the extrinsic information in the messages sent from the variable nodes. Its variable node equation is reformulated to reduce its complexity. Both algorithms were tested for the (2048,1723) RS-based LDPC code and (16129,15372) LDPC code using an FPGA-based hardware emulator. They exhibit BER performance very close to Min-Sum algorithm and do not introduce early error-floor. \n\nIn order to show the hardware advantages of the proposed algorithms, hardware decoders were implemented in a 90 nm CMOS process and FPGA devices based on two types of architectures: full-parallel and partial-parallel one with horizontal layered schedule. The results show that the decoders are more area-time efficient than other published decoders and that the low-complexity of the Modified Optimized 2-bit Min-Sum allows the implementation of 10 Gbps decoders in current FPGA devices. \n\nFinally, a new hard-decision decoding algorithm, the Historical-Extrinsic Reliability-Based Iterative Decoder, is presented. This algorithm introduces the new idea of considering hard-decision votes as soft-decision to compute the extrinsic information of previous iterations. It is suitable for high-rate codes and improves the BER performance of the previous RBI-MLGD algorithms, with similar complexity.
Abstract ― Low Density Parity Check (LDPC) code approaches Shannon–limit performance for binary field and long code lengths. However, performance of binary LDPC code is degraded when the code word length is small. An optimized min-sum algorithm for LDPC code is proposed in this paper. In this algorithm unlike other decoding methods, an optimization factor has been introduced in both check node and bit node of the Min-sum algorithm. The optimization factor is obtained before decoding program, and the same factor is multiplied twice in one cycle. So the increased complexity is fairly low. Simulation results show that the proposed Optimized Min-Sum decoding algorithm performs very close to the Sum-Product decoding while preserving the main features of the Min-Sum decoding, that is low complexity and independence with respect to noise variance estimation errors.
Many classes of high-performance Low-density parity check codes are based on parity check matrices composed of permutation sub matrices. The emulation-simulation framework further allows the algorithm and implementation to be iteratively redefined to improve the error floor performance of message passing decoder. Log-Like hood-Ratio (LLR) based Belief-Propagation (BP) algorithm is presented for Low Density Parity Check codes. Numerically accurate representation of check node update computation used in LLR-BP decoding is described. The implementation of Sum-Product algorithm (SPA) within Low Density Parity Check Code (LDPC) decoder is described in this paper and the correction term is used to improve the decoding performance of min-sum algorithm (MSA). Quantization and log-tanh function approximation in sum-product decoder strongly affect which absorbing set dominates in error floor region. For LDPC decoder, bit error rate (BER) decreases with increase in the signal to noise ratio.