Low-complexity Decoding Algorithms and Architectures for Non-binary LDPC Codes

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Release : 2013
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Low-complexity Decoding Algorithms and Architectures for Non-binary LDPC Codes - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Low-complexity Decoding Algorithms and Architectures for Non-binary LDPC Codes write by Fang Cai. This book was released on 2013. Low-complexity Decoding Algorithms and Architectures for Non-binary LDPC Codes available in PDF, EPUB and Kindle. Non-binary low-density parity-check (NB-LDPC) codes can achieve better error-correcting performance than their binary counterparts when the code length is moderate at the cost of higher decoding complexity. The high complexity is mainly caused by the complicated computations in the check node processing and the large memory requirement. In this thesis, three decoding algorithms and corresponding VLSI architectures are proposed for NB-LDPC codes to lower the computational complexity and memory requirement. The first design is based on the proposed relaxed Min-max decoding algorithm. A novel relaxed check node processing scheme is proposed for the Min-max NB-LDPC decoding algorithm. Each finite field element of GF(2p̂) can be uniquely represented by a linear combination of $p$ independent field elements. Making use of this property, an innovative method is developed in this paper to first find a set of the p most reliable variable-to-check messages with independent field elements, called the minimum basis. Then the check-to-variable messages are efficiently computed from the minimum basis. With very small performance loss, the complexity of the check node processing can be substantially reduced using the proposed scheme. In addition, efficient VLSI architectures are developed to implement the proposed check node processing and overall NB-LDPC decoder. Compared to the most efficient prior design, the proposed decoder for a (837, 726) NB-LDPC code over GF(25̂) can achieve 52% higher efficiency in terms of throughput-over-area ratio. The second design is based on a proposed enhanced iterative hard reliability-based majority-logic decoding. The recently developed iterative hard reliability-based majority-logic NB-LDPC decoding has better performance-complexity tradeoffs than previous algorithms. Novel schemes are proposed for the iterative hard reliability-based majority-logic decoding (IHRB-MLGD). Compared to the IHRB algorithm, our enhanced (E- )IHRB algorithm can achieve significant coding gain with small hardware overhead. Then low-complexity partial-parallel NB-LDPC decoder architectures are developed based on these two algorithms. Many existing NB-LDPC code construction methods lead to quasi-cyclic or cyclic codes. Both types of codes are considered in our design. Moreover, novel schemes are developed to keep a small proportion of messages in order to reduce the memory requirement without causing noticeable performance loss. In addition, a shift-message structure is proposed by using memories concatenated with variable node units to enable efficient partial-parallel decoding for cyclic NB-LDPC codes. Compared to previous designs based on the Min-max decoding algorithm, our proposed decoders have at least tens of times lower complexity with moderate coding gain loss. The third design is based on a proposed check node decoding scheme using power representation of finite field elements. Novel schemes are proposed for the Min-max check node processing by making use of the cyclical-shift property of the power representation of finite field elements. Compared to previous designs based on the Min-max algorithm with forward-backward scheme, the proposed check node units (CNUs) do not need the complex switching network. Moreover, the multiplications of the parity check matrix entries are efficiently incorporated. For a Min-max NB-LDPC decoder over GF(32), the proposed scheme reduces the CNU area by at least 32%, and leads to higher clock frequency.

High-Performance and Energy-Efficient Decoder Design for Non-Binary LDPC Codes

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Release : 2016
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High-Performance and Energy-Efficient Decoder Design for Non-Binary LDPC Codes - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook High-Performance and Energy-Efficient Decoder Design for Non-Binary LDPC Codes write by Yuta Toriyama. This book was released on 2016. High-Performance and Energy-Efficient Decoder Design for Non-Binary LDPC Codes available in PDF, EPUB and Kindle. Binary Low-Density Parity-Check (LDPC) codes are a type of error correction code known to exhibit excellent error-correcting capabilities, and have increasingly been applied as the forward error correction solution in a multitude of systems and standards, such as wireless communications, wireline communications, and data storage systems. In the pursuit of codes with even higher coding gain, non-binary LDPC (NB-LDPC) codes defined over a Galois field of order q have risen as a strong replacement candidate. For codes defined with similar rate and length, NB-LDPC codes exhibit a significant coding gain improvement relative to that of their binary counterparts. Unfortunately, NB-LDPC codes are currently limited from practical application by the immense complexity of their decoding algorithms, because the improved error-rate performance of higher field orders comes at the cost of increasing decoding algorithm complexity. Currently available ASIC implementation solutions for NB-LDPC code decoders are simultaneously low in throughput and power-hungry, leading to a low energy efficiency. We propose several techniques at the algorithm level as well as hardware architecture level in an attempt to bring NB-LDPC codes closer to practical deployment. On the algorithm side, we propose several algorithmic modifications and analyze the corresponding hardware cost alleviation as well as impact on coding gain. We also study the quantization scheme for NB-LDPC decoders, again in the context of both the hardware and coding gain impacts, and we propose a technique that enables a good tradeoff in this space. On the hardware side, we develop a FPGA-based NB-LDPC decoder platform for architecture prototyping as well as hardware acceleration of code evaluation via error rate simulations. We also discuss the architectural techniques and innovations corresponding to our proposed algorithm for optimization of the implementation. Finally, a proof-of-concept ASIC chip is realized that integrates many of the proposed techniques. We are able to achieve a 3.7x improvement in the information throughput and 23.8x improvement in the energy efficiency over prior state-of-the-art, without sacrificing the strong error correcting capabilities of the NB-LDPC code.

Optimizing and Decoding LDPC Codes with Graph-based Techniques

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Release : 2010
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Book Rating : 071/5 ( reviews)

Optimizing and Decoding LDPC Codes with Graph-based Techniques - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Optimizing and Decoding LDPC Codes with Graph-based Techniques write by Amir H. Djahanshahi. This book was released on 2010. Optimizing and Decoding LDPC Codes with Graph-based Techniques available in PDF, EPUB and Kindle. Low-density parity-check (LDPC) codes have been known for their outstanding error-correction capabilities. With low-complexity decoding algorithms and a near capacity performance, these codes are among the most promising forward error correction schemes. LDPC decoding algorithms are generally sub-optimal and their performance not only depends on the codes, but also on many other factors, such as the code representation. In particular, a given non-binary code can be associated with a number of different field or ring image codes. Additionally, each LDPC code can be described with many different Tanner graphs. Each of these different images and graphs can possibly lead to a different performance when used with iterative decoding algorithms. Consequently, in this dissertation we try to find better representations, i.e., graphs and images, for LDPC codes. We take the first step by analyzing LDPC codes over multiple-input single-output (MISO) channels. In an n_T by 1 MISO system with a modulation of alphabet size 2^M, each group of n_T transmitted symbols are combined and produce one received symbol at the receiver. As a result, we consider the LDPC-coded MISO system as an LDPC code over a 2^{M n_T}-ary alphabet. We introduce a modified Tanner graph to represent MISO-LDPC systems and merge the MISO symbol detection and binary LDPC decoding steps into a single message passing decoding algorithm. We present an efficient implementation for belief propagation decoding that significantly reduces the decoding complexity. With numerical simulations, we show that belief propagation decoding over modified graphs outperforms the conventional decoding algorithm for short length LDPC codes over unknown channels. Subsequently, we continue by studying images of non-binary LDPC codes. The high complexity of belief propagation decoding has been proven to be a detrimental factor for these codes. Thereby, we suggest employing lower complexity decoding algorithms over image codes instead. We introduce three classes of binary image codes for a given non-binary code, namely: basic, mixed, and extended binary image codes. We establish upper and lower bounds on the minimum distance of these binary image codes, and present two techniques to find binary image codes with better performance under belief propagation decoding algorithm. In particular, we present a greedy algorithm to find optimized binary image codes. We then proceed by investigation of the ring image codes. Specifically, we introduce matrix-ring-image codes for a given non-binary code. We derive a belief propagation decoding algorithm for these codes, and with numerical simulations, we demonstrate that the low-complexity belief propagation decoding of optimized image codes has a performance very close to the high complexity BP decoding of the original non-binary code. Finally, in a separate study, we investigate the performance of iterative decoders over binary erasure channels. In particular, we present a novel approach to evaluate the inherent unequal error protection properties of irregular LDPC codes over binary erasure channels. Exploiting the finite length scaling methodology, that has been used to study the average bit error rate of finite-length LDPC codes, we introduce a scaling approach to approximate the bit erasure rates in the waterfall region of variable nodes with different degrees. Comparing the bit erasure rates obtained from Monte Carlo simulation with the proposed scaling approximations, we demonstrate that the scaling approach provides a close approximation for a wide range of code lengths. In view of the complexity associated with the numerical evaluation of the scaling approximation, we also derive simpler upper and lower bounds and demonstrate through numerical simulations that these bounds are very close to the scaling approximation.

Low Complexity Decoding of Non-binary LDPC Codes Over AWGN Channels

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Release : 2009
Genre : Decoders (Electronics)
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Low Complexity Decoding of Non-binary LDPC Codes Over AWGN Channels - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Low Complexity Decoding of Non-binary LDPC Codes Over AWGN Channels write by Pia Aviva Zobel. This book was released on 2009. Low Complexity Decoding of Non-binary LDPC Codes Over AWGN Channels available in PDF, EPUB and Kindle.

Efficient VLSI Architectures for Non-binary Low Density Parity Check Decoding

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Release : 2011
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Efficient VLSI Architectures for Non-binary Low Density Parity Check Decoding - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Efficient VLSI Architectures for Non-binary Low Density Parity Check Decoding write by Fang Cai. This book was released on 2011. Efficient VLSI Architectures for Non-binary Low Density Parity Check Decoding available in PDF, EPUB and Kindle. Non-binary low-density parity-check (NB-LDPC) codes can achieve better error-correcting performance than binary LDPC codes when the code length is moderate at the cost of higher decoding complexity. The high complexity is mainly caused by the complicated computations in the check node processing and the large memory requirement. In this thesis, two VLSI designs for NB-LDPC decoders based on two novel check node processing schemes are proposed. The first design is based on forward-backward check node processing. A novel scheme and corresponding architecture are developed to implement the elementary step of the check node processing. In our design, layered decoding is applied and only nm less than q messages are kept on each edge of the associated Tanner graph. The computation units and the scheduling of the computations are optimized in the context of layered decoding to reduce the area requirement and increase the speed. This thesis also introduces an overlapped method for the check node processing among different layers to further speed up the decoding. From complexity and latency analysis, our design is much more efficient than any previous design. Our proposed decoder for a (744, 653) code over GF(32) has also been synthesized on a Xilinx Virtex-2 Pro FPGA device. It can achieve a throughput of 9.30 Mbps when 15 decoding iterations are carried out. The second design is based on a proposed trellis based check node processing scheme. The proposed scheme first sorts out a limited number of the most reliable variable-to-check (v-to-c) messages, then the check-to-variable (c-to-v) messages to all connected variable nodes are derived independently from the sorted messages without noticeable performance loss. Compared to the previous iterative forward-backward check node processing, the proposed scheme not only significantly reduced the computation complexity, but eliminated the memory required for storing the intermediate messages generated from the forward and backward processes. Inspired by this novel c-to-v message computation method, we propose to store the most reliable v-to-c messages as 'compressed' c-to-v messages. The c-to-v messages will be recovered from the compressed format when needed. Accordingly, the memory requirement of the overall decoder can be substantially reduced. Compared to the previous Min-max decoder architecture, the proposed design for a (837, 726) code over GF(32) can achieve the same throughput with only 46% of the area.