检索结果-内蒙古大学图书馆

Design of Irregular LDPC Codes for BIAWGN Channels with SNR Mismatch

IEEE TRANSACTIONS ON COMMUNICATIONS 2009年第1期57卷 6-11页

作者： Saeedi, Hamid Banihashemi, Amir H. Carleton Univ Dept Syst & Comp Engn Broadband Commun & Wireless Syst BCWS Ctr Ottawa ON K1S 5B6 Canada

Belief propagation (BP) algorithm for decoding low-density parity-check (LDPC) codes over a binary input additive white Gaussian noise (BIAWGN) channel requires the knowledge of the signal-to-noise ratio (SNR) at the receiver to achieve its ultimate performance. An erroneous estimation or the absence of a perfect knowledge of the SNR at the decoder is referred to as "SNR mismatch". SNR mismatch can significantly degrade the performance of LDPC codes decoded by the BP algorithm. In this paper, using extrinsic information transfer (EXIT) charts, we design irregular LDPC codes that perform better (have a lower SNR threshold) in the presence of mismatch compared to the conventionally designed irregular LDPC codes that are optimized for zero mismatch. Considering that min-sum (MS) algorithm is the limit of BP with infinite SNR over-estimation, the EXIT functions generated in this work can also be used for the efficient analysis and design of LDPC codes under the MS algorithm.

关键词： Irregular LDPC codes signal-to-noise ratio (SNR) mismatch channel estimation error LDPC code design EXIT charts belief propagation (BP) algorithm min-sum algorithm

来源：评论

学校读者我要写书评

暂无评论

NOLD: A Neural-Network Optimized Low-Resolution Decoder for LDPC Codes

引用

JOURNAL OF COMMUNICATIONS AND NETWORKS 2021年第3期23卷 159-170页

作者： Chu, Lei He, Huanyu Pei, Ling Qiu, Robert C. Shanghai Jiao Tong Univ Sch Elect Informat & Elect Engn Shanghai 200240 Peoples R China

The min-sum (MS) algorithm can decode Low-density parity-check (LDPC) codes with low computational complexity at the cost of slight performance loss. It is an effective way to realize hardware implementation of the min-sum decoder by quantizing the floating belief messages (i.e., check-to-variable messages and variable-to-check messages) into low-resolution (i.e., 2-4 bits) versions. However, such a way can lead to severe performance degradation due to the finite precision effect. In this paper, we propose a neural-network optimized low-resolution decoding (NOLD) algorithm for LDPC codes to deal with the problem. Specifically, the optimization of decoding parameters (i.e., scaling factors and quantization step) is achieved in a hybrid way, in which we concatenate a NOLD decoder with a customized neural network. All learnable parameters associated with the decoding parameters are assigned to each neuron in the proposed method. What's more, we design a new activation function whose outputs are close to the employed quantizer ones when network parameters are finally optimized off-line. Finally, the performance of the proposed method is verified by numerous experiments. For the case of 2-bit decoding, the proposed approach significantly outperforms several conventional decoders at the expense of slightly increased off-line training time. Besides, the proposed method with 4-bit quantization incurs only 0.1 dB performance loss compared with the floating min-sum decoder at the coded bit-error-rate of 10(-5). Moreover, we show that the proposed NOLD decoder works over a wide range of channel conditions for regular and irregular LDPC codes. Simulation code for reproductive results is publicly available(1).

关键词： Low-density parity-check codes low-resolution min-sum algorithm neural network optimization

来源：评论

学校读者我要写书评

暂无评论

A decoding algorithm for finite-geometry LDPC codes

引用

IEEE TRANSACTIONS ON COMMUNICATIONS 2005年第3期53卷 415-421页

作者： Liu, ZY Pados, DA SUNY Buffalo Dept Elect Engn Buffalo NY 14260 USA

In this paper, we develop a new low-complexity algorithm to decode low-density parity-check (LDPC) codes. The developments are oriented specifically toward low-cost, yet effective, decoding of (high-rate) finite-geometry (FG) LDPC codes. The decoding procedure updates iteratively the hard-decision received vector in search of a valid codeword in the vector space. Only one bit is changed in each iteration, and the bit-selection criterion combines the number of failed checks and the reliability of the received bits. Prior knowledge of the signal amplitude and noise power is not required. An optional mechanism to avoid infinite loops in the search is also proposed. Our studies show that the algorithm achieves an appealing tradeoff between performance and complexity for FG-LDPC codes.

关键词： belief propagation (BP) bit-flipping (BF) decoding block codes cyclic codes low-density parity-check (LDPC) codes min-sum algorithm soft-decision decoding sum-product algorithm (SPA)

来源：评论

学校读者我要写书评

暂无评论

Self-compensation technique for simplified belief-propagation algorithm

引用

IEEE TRANSACTIONS ON SIGNAL PROCESSING 2007年第6期55卷 3061-3072页

作者： Liao, Yen-Chin Lin, Chien-Ching Chang, Hsie-Chia Liu, Chih-Wei Natl Chiao Tung Univ Dept Elect Engn Hsinchu 30039 Taiwan

The min-sum algorithm is the most common method to simplify the belief-propagation algorithm for decoding low-density parity-check (LDPC) codes. However, there exists a performance gap between the min-sum and belief-propagation algorithms due to nonlinear approximation. In this paper, a self-compensation technique using dynamic normalization is thus proposed to improve the approximation accuracy. The proposed scheme scales the min-sum algorithm by a dynamic factor that can be derived theoretically from order statistics. Moreover, applying the proposed technique to several LDPC codes for DVB-S2 system, the average signal-to-noise ratio degradation, which results from approximation inaccuracy and quantization error, is reduced to 0.2 dB. Not only does it enhance the error-correcting capability of the min-sum algorithm, but the proposed self-compensation technique also preserves a modest hardware cost. After realized with 0.13-mu m standard cell library, the dynamic normalization requires about 100 additional gates for each check,node unit in the min-sum algorithm.

关键词： belief-propagation dynamic normalization iterative decoding low-density parity-check (LDPC) codes min-sum algorithm self compensation

来源：评论

学校读者我要写书评

暂无评论

Low-density parity-check lattices: Construction and decoding analysis

引用

IEEE TRANSACTIONS ON INFORMATION THEORY 2006年第10期52卷 4481-4495页

作者： Sadeghi, Mohammad-Reza Banihashemi, Amir H. Panario, Daniel Amirkabir Univ Technol Fac Math & Comp Sci Tehran Iran Carleton Univ Dept Syst & Comp Engn BCWS Ctr Ottawa ON K1S 5B6 Canada Carleton Univ Sch Math & Stat Ottawa ON K1S 5B6 Canada

Low-density parity-check codes (LDPC) can have an impressive performance under iterative decoding algorithms. In this paper we introduce a method to construct high coding gain lattices with low decoding complexity based on LDPC codes. To construct such lattices we apply Construction D', due to Bos, Conway, and Sloane, to a set of parity checks defining a family of nested LDPC codes. For the decoding algorithm, we generalize the application of max-sum algorithm to the Tanner graph of lattices. Bounds on the decoding complexity are derived and our analysis shows that using LDPC codes results in low decoding complexity for the proposed lattices. The progressive edge growth (PEG) algorithm is then extended to construct a class of nested regular LDPC codes which are in turn used to generate low density parity check lattices. Using this approach, a class of two-level lattices is constructed. The performance of this class improves when the dimension increases and is within 3 dB of the Shannon limit for error probabilities of about 10(-6). This is while the decoding complexity is still quite manageable even for dimensions of a few thousands.

关键词： additive white Gaussian noise (AWGN) channel iterative decoding lattice codes lattices low-density parity-check (LDPC) codes low-density parity-check (LDPC) lattices min-sum algorithm progressive-edge growth (PEG) construction Tanner graphs

来源：评论

学校读者我要写书评

暂无评论

High performance short-block binary regular LDPC codes

引用

ALEXANDRIA ENGINEERING JOURNAL 2018年第4期57卷 2633-2639页

作者： Mostari, Latifa Taleb-Ahmed, Abdelmalik Hassiba Benbouali Univ Chlef Fac Technol Dept Elect Chlef Algeria Univ Valenciennes & Hainaut Combresis LAMIH UMR CNRS 8201 Valenciennes France

LDPC code shows a good performance with long-block codes. However, certain channels are constrained to use short-block codes due to latency. Therefore, concatenated LDPC codes with iterative decoding is a good choice to get a good performance. Concatenated binary LDPC codes were introduced as a class of concatenated codes in which the LDPC codes are irregular codes having different parameters. Although irregular LDPC codes are more efficient than regular codes, irregular LDPC codes have an error floor and a higher encoding complexity than regular code. In this paper, in order to get a good performance/complexity trade-off with a short-block code, we investigate a parallel concatenation of two identical regular binary LDPC codes, using an inter-leaver. Simulation results show that the proposed code outperforms a single LDPC code. The proposed code needs less time decoding delay than a single LDPC code with the same iteration number. Also, the proposed code needs a less number of iterations to achieve the same performance of a single LDPC code that leads to less decoding complexity and decoding delay. A simplified algorithm, the min-sum algorithm, that is used to decode the component codes shows a small performance loss with respect to the sum-product algorithm. (C) 2018 Faculty of Engineering, Alexandria University. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： LDPC code Parallel concatenation Iterative decoding sum-product algorithm min-sum algorithm

来源：评论

学校读者我要写书评

暂无评论

Convergence and correctness of belief propagation for the Chinese postman problem

引用

JOURNAL OF GLOBAL OPTIMIZATION 2019年第3期75卷 813-831页

作者： Dai, Guowei Li, Fengwei Sun, Yuefang Xu, Dachuan Zhang, Xiaoyan Nanjing Normal Univ Inst Math Nanjing 210023 Jiangsu Peoples R China Nanjing Normal Univ Sch Math Sci Nanjing 210023 Jiangsu Peoples R China Cent China Normal Univ Fac Math & Stat Wuhan 430079 Hubei Peoples R China Shaoxing Univ Dept Math Shaoxing 312000 Peoples R China Beijing Univ Technol Dept Informat & Operat Res Coll Appl Sci Beijing 100124 Peoples R China

Belief Propagation (BP), a distributed, message-passing algorithm, has been widely used in different disciplines including information theory, artificial intelligence, statistics and optimization problems in graphical models such as Bayesian networks and Markov random fields. Despite BP algorithm has a great success in many application fields and many progress about BP algorithm has been made, the rigorous analysis about the correctness and convergence of BP algorithm are known in only a few cases for arbitrary graph. In this paper, we will investigate the correctness and convergence of BP algorithm for determining the optimal solutions of the Chinese postman problem in both undirected and directed graphs. As a main result, we prove that BP algorithm converges to the optimal solution of the undirected Chinese postman problem within O(n) iterations where n represents the number of vertices, provided that the optimal solution is unique. For the directed case, we consider the directed Chinese postman problem with capacity and show that BP algorithm also converges to its optimal solution after O(n) iterations, as long as its corresponding linear programming relaxation has the unique optimal solution.

关键词： Belief propagation (BP) Message-passing algorithm min-sum algorithm Convergence Undirected Chinese postman problem Directed Chinese postman problem

来源：评论

学校读者我要写书评

暂无评论

On Decoding Irregular Tanner Codes With Local-Optimality Guarantees

引用

IEEE TRANSACTIONS ON INFORMATION THEORY 2014年第1期60卷 191-211页

作者： Halabi, Nissim Even, Guy Tel Aviv Univ Sch Elect Engn IL-69978 Tel Aviv Israel

We consider decoding of binary linear Tanner codes using message-passing iterative decoding and linear-programming (LP) decoding in memoryless binary-input output-symmetric (MBIOS) channels. We present new certificates that are based on a combinatorial characterization for the local optimality of a codeword in irregular Tanner codes with respect to any MBIOS channel. This characterization is a generalization of (Arora et al., Proc. ACM Symp. Theory of Computing, 2009) and (Vontobel, Proc. Inf. Theory and Appl. Workshop, 2010) and is based on a conical combination of normalized weighted subtrees in the computation trees of the Tanner graph. These subtrees may have any finite height (even equal or greater than half of the girth of the Tanner graph). In addition, the degrees of local-code nodes in these subtrees are not restricted to two (i.e., these subtrees are not restricted to skinny trees). We prove that local optimality in this new characterization implies maximum-likelihood (ML) optimality and LP optimality, and show that a certificate can be computed efficiently. We also present a new message-passing iterative decoding algorithm, called normalized weighted min-sum (NWMS). NWMS decoding is a belief-propagation (BP) type algorithm that applies to any irregular binary Tanner code with single parity-check local codes (e. g., low-density and high-density parity-check codes). We prove that if a locally optimal codeword with respect to height parameter exists (whereby notably is not limited by the girth of the Tanner graph), then NWMS decoding finds this codeword in iterations. The decoding guarantee of the NWMS decoding algorithm applies whenever there exists a locally optimal codeword. Because local optimality of a codeword implies that it is the unique ML codeword, the decoding guarantee also provides an ML certificate for this codeword. Finally, we apply the new local-optimality characterization to regular Tanner codes, and prove lower bounds on the noise threshol

关键词： Error bounds factor graphs graph cover IDPC codes linear programming (LP) decoding local optimality max-product algorithm maximum-likelihood (ML) certificate memoryless binary-input output-symmetric (MBIOS) channel message-passing algorithms min-sum algorithm Tanner codes thresholds

来源：评论

学校读者我要写书评

暂无评论

Resource Allocation via Message Passing

引用

INFORMS JOURNAL ON COMPUTING 2011年第2期23卷 205-219页

作者： Moallemi, Ciamac C. Van Roy, Benjamin Columbia Univ Grad Sch Business New York NY 10027 USA Stanford Univ Dept Management Sci & Engn Stanford CA 94305 USA

We propose a message-passing paradigm for resource allocation problems. This serves to connect ideas from the message-passing literature, which has primarily grown out of the communications, statistical physics, and artificial intelligence communities, with a problem central to operations research. This also provides a new framework for decentralized management that generalizes price-based systems by allowing incentives to vary across activities and consumption levels. We demonstrate that message-based incentives, which are characterized by a new equilibrium concept, lead to system-optimal behavior for convex resource allocation problems yet yield allocations superior to those from price-based incentives for nonconvex problems. We describe a distributed and asynchronous message-passing algorithm for computing equilibrium messages and allocations, and we demonstrate its merits in the context of a network resource allocation problem.

关键词： message-passing algorithms min-sum algorithm resource allocation convex optimization decentralized optimization

来源：评论

学校读者我要写书评

暂无评论

Cost-effective variable node using thermalcode addition for LDPC decoders

引用

IEICE ELECTRONICS EXPRESS 2011年第23期8卷 1948-1953页

作者： Yang, Po-Hui Liu, Jia-Ping Natl Yunlin Univ Sci & Technol Dept Elect Engn Yunlin 640 Taiwan

The current paper presents thermalcode addition technology as applied to an LDPC decoder to replace a variable node unit in the traditional adder. The proposed irregular quantization of thermalcode addition can generate information with regularity, which makes addition to the variable node executable by combinational logic circuit. With the original BER performance, code rate 1/2, and matrix (1296,648) in 802.11n standard, the simulation and logic synthesis results reveal that the presented LDPC decoder can save up to 21% of the hardware area.

关键词： LDPC decoder min-sum algorithm variable node

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：