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Author:
Publisher:
ISBN:
Category : Decoders (Electronics)
Languages : en
Pages : 55
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Book Description
Author:
Publisher:
ISBN:
Category : Decoders (Electronics)
Languages : en
Pages : 55
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Book Description
Author: Vikram Arkalgud Chandrasetty
Publisher: Academic Press
ISBN: 0128112565
Category : Technology & Engineering
Languages : en
Pages : 192
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Book Description
This book takes a practical hands-on approach to developing low complexity algorithms and transforming them into working hardware. It follows a complete design approach – from algorithms to hardware architectures - and addresses some of the challenges associated with their design, providing insight into implementing innovative architectures based on low complexity algorithms.The reader will learn: Modern techniques to design, model and analyze low complexity LDPC algorithms as well as their hardware implementation How to reduce computational complexity and power consumption using computer aided design techniques All aspects of the design spectrum from algorithms to hardware implementation and performance trade-offs Provides extensive treatment of LDPC decoding algorithms and hardware implementations Gives a systematic guidance, giving a basic understanding of LDPC codes and decoding algorithms and providing practical skills in implementing efficient LDPC decoders in hardware Companion website containing C-Programs and MATLAB models for simulating the algorithms, and Verilog HDL codes for hardware modeling and synthesis
Author:
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ISBN:
Category :
Languages : en
Pages : 6
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Book Description
This paper describes the implementation of a general and embedded decoder for the evaluation of unstructured low-density parity-check (LDPC) codes over additive-white Gaussian noise (AWGN) channels. The decoder, which has a serial architecture and moderate throughput, is a peripheral connected to the embedded PowerPC processor of a Xilinx Virtex-II Pro FPGA and is managed by the processor. This method of Hardware/ Software implementation provides the maximum flexibility for the development and rapid prototyping of the hardware-based simulator system. The decoding algorithm proposed in this paper belongs to the class of min-sum with correction factor in which the correction factor updates with the log-likelihood ratio (LLR) values.
Author: Manpreet Singh
Publisher:
ISBN:
Category :
Languages : en
Pages : 73
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Book Description
Low-density parity-check (LDPC) codes are a class of easily decodable error-correcting codes. Published parallel LDPC decoders demonstrate high throughput and low energy-per-bit but require a lot of silicon area. Decoders based on digit-online arithmetic (processing several bits per fundamental operation) process messages in a digit-serial fashion, reducing the area requirements, and can process multiple frames in frame-interlaced fashion. Implementations on Field-Programmable Gate Array (FPGA) are usually power- and area-hungry, but provide flexibility compared with application-specific integrated circuit implementations. With the penetration of mobile devices in the electronics industry the power considerations have become increasingly important. The power consumption of a digit-online decoder depends on various factors, like input log-likelihood ratio (LLR) bit precision, signal-to-noise ratio (SNR) and maximum number of iterations. The design is implemented on an Altera Stratix IV GX EP4SGX230 FPGA, which comes on an Altera DE4 Development and Education Board. In this work, both parallel and digit-online block LDPC decoder implementations on FPGAs for WiMAX 576-bit, rate-3/4 codes are studied, and power measurements from the DE4 board are reported. Various components of the system include a random-data generator, WiMAX Encoder, shift-out register, additive white Gaussian noise (AWGN) generator, channel LLR buffer, WiMAX Decoder and bit-error rate (BER) Calculator. The random-data generator outputs pseudo-random bit patterns through an implemented linear-feedback shift register (LFSR). Digit-online decoders with input LLR precisions ranging from 6 to 13 bits and parallel decoders with input LLR precisions ranging from 3 to 6 bits are synthesized in a Stratix IV FPGA. The digit-online decoders can be clocked at higher frequency for higher LLR precisions. A digit-online decoder can be used to decode two frames simultaneously in frame-interlaced mode. For the 6-bit implementation of digit-online decoder in single-frame mode, the minimum throughput achieved is 740 Mb/s at low SNRs. For the case of 11-bit LLR digit-online decoder in frame-interlaced mode, the minimum throughput achieved is 1363 Mb/s. Detailed analysis such as effect of SNR and LLR precision on decoder power is presented. Also, the effect of changing LLR precision on max clock frequency and logic utilization on the parallel and the digit-online decoders is studied. Alongside, power per iteration for a 6-bit LLR input digit-online decoder is also reported.
Author: Reza Nakhjavani
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
The exponential growth of digital data has led to the proliferation of cloud storage systems as well as high-capacity, low-latency storage devices such as flash memory based solid-state drives (SSDs). These advances, along with the technology shrink, have increased the error rate both at system and device level. Storage device manufacturers and service providers often promise data reliability through error control coding. This dissertation is centered around the implementation of error correcting code (ECC) in data storage. In particular, we target low-density parity-check (LDPC) codes used for device-level and erasure codes used for system-level data reliability. Due to the ever-changing ECC requirements in the storage industry, we focus on field programmable gate arrays (FPGAs), given their short design cycles. Many studies on FPGA implementation of ECC focus on improving the hardware efficiency for a certain code of interest. This thesis extends this theme by considering hardware and code performance simultaneously. With the focus on ECCs used in data storage, we demonstrate a study of hardware-code co-design through an efficient FPGA micro-architecture that strikes a trade off between hardware efficiency and code performance. To this end, we leverage the FPGA's inherent physical architecture to propose an efficient reconfigurable micro-architecture for LDPC decoders. Then, we address the limitations of ECC in flash memories and define a finite decoder design space. Finally, we propose an end-to-end solution in which we leverage machine learning techniques to design a finite alphabet iterative decoder which strikes a trade off between hardware efficiency and code performance. In a separate effort, we perform a quantitative study of erasure coding design on FPGAs. We demonstrate, through probabilistic analysis, that an efficient implementation ought to allocate more resources to the common-case, while reducing the performance target for less probable cases.
Author: Weihuang Wang
Publisher:
ISBN:
Category :
Languages : en
Pages :
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This thesis presents a low-power LDPC decoder design based on speculative scheduling of energy necessary to decode dynamically varying data frame in both block-fading channels and general AWGN channels. A model of a memory-efficient low-power high-throughput multi-rate array LDPC decoder as well as its FPGA implementation results is first presented. Then, I propose a decoding scheme that provides the feature of constant-time decoding and thus facilitates real-time applications where guaranteed data rate is required. It pre-analyzes each received data frame to estimate the maximum number of necessary iterations for frame convergence. The results are then used to dynamically adjust decoder frequency and switch between multiple-voltage levels; thereby energy use is minimized. This is in contrast to the conventional fixed-iteration decoding schemes that operate at a fixed voltage level regardless of the quality of data received. Analysis shows that the proposed decoding scheme is widely applicable for both two-phase message-passing (TPMP) decoding algorithm and turbo decoding message passing (TDMP) decoding algorithm in block fading channels, and it is independent of the specific LDPC decoder architecture. A decoder architecture utilizing our recently published multi-rate decoding architecture for general AWGN channels is also presented. The result of this thesis is a decoder design scheme that provides a judicious trade-off between power consumption and coding gain.
Author: Yifei Zhang
Publisher:
ISBN:
Category :
Languages : en
Pages : 254
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Low-density parity-check (LDPC) codes have been intensively studied in the past decade for their capacity-approaching performance. LDPC code implementation complexity and the error-rate floor are still two significant unsolved issues which prevent their application in some important communication systems. In this dissertation, we make efforts toward solving these two problems by introducing the design of a class of LDPC codes called structured irregular repeat-accumulate (S-IRA) codes. These S-IRA codes combine several advantages of other types of LDPC codes, including low encoder and decoder complexities, flexibility in design, and good performance on different channels. It is also demonstrated in this dissertation that the S-IRA codes are suitable for rate-compatible code family design and a multi-rate code family has been designed which may be implemented with a single encoder/decoder. The study of the error floor problem of LDPC codes is very difficult because simulating LDPC codes on a computer at very low error rates takes an unacceptably long time. To circumvent this difficulty, we implemented a universal quasi-cyclic LDPC decoder on a field programmable gate array (FPGA) platform. This hardware platform accelerates the simulations by more than 100 times as compared to software simulations. We implemented two types of decoders with partially parallel architectures on the FPGA: a circulant-based decoder and a protograph-based decoder. By focusing on the protograph-based decoder, different soft iterative decoding algorithms were implemented. It provides us with a platform for quickly evaluating and analyzing different quasi-cyclic LDPC codes, including the S-IRA codes. A universal decoder architecture is also proposed which is capable of decoding of an arbitrary LDPC code, quasi-cyclic or not. Finally, we studied the low-floor problem by focusing on one example S-IRA code. We identified the weaknesses of the code andproposed several techniques to lower the error floor. We successfully demonstrated in hardware that it is possible to lower the floor substantially by encoder and decoder modifications, but the best solution appeared to be an outer BCH code.
Author: Kung Chi Cinnati Loi
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Xiaoheng Chen
Publisher:
ISBN: 9781124906669
Category :
Languages : en
Pages :
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Book Description
Since the rediscovery of low-density parity-check (LDPC) codes in the late 1990s, tremendous progress has been made in code construction and design, decoding algorithms, and decoder implementation of these capacity-approaching codes. Recently, LDPC codes are considered for applications such as high-speed satellite and optical communications, the hard disk drives, and high-density flash memory based storage systems, which require that the codes are free of error-floor down to bit error rate (BER) as low as 10−12 to 10−15. FPGAs are usually used to evaluate the error performance of codes, since one can exploit the finite word length and extremely high internal memory bandwidth of an FPGA. Existing FPGA-based LDPC decoders fail to utilize the configurability and read-first mode of embedded memory in the FPGAs, and thus result in limited throughput and codes sizes. Four optimization techniques, i.e., vectorization, folding, message relocation, and circulant permutation matrix (CPM) sharing, are proposed to improve the throughput, scalability, and efficiency of FPGA-based decoders. Also, a semi-automatic CAD tool called QCSYN (Quasi-Cyclic LDPC decoder SYNthesis) is designed to shorten the implementation time of decoders. Using the above techniques, a high-rate (16129,15372) code is shown to have no error-floor down to the BER of 10−14. Also, it is very difficult to construct codes that do not exhibit an error floor down to 10−15 or so. Without detailed knowledge of dominant trapping sets, a backtracking-based reconfigurable decoder is designed to lower the error floor of a family of structurally compatible quasi-cyclic LDPC codes by one to two orders of magnitudes. Hardware reconfigurability is another significant feature of LDPC decoders. A tri-mode decoder for the (4095,3367) Euclidean geometry code is designed to work with three compatible binary message passing decoding algorithms. Note that this code contains 262080 edges (21.3 times of the (2048,1723) 10GBASE-T code) in its Tanner graph and is the largest code ever implemented. Besides, an efficient QC-LDPC Shift Network (QSN) is proposed to reduce the interconnect delay and control logic of circular shift network, a core component in the reconfigurable decoder that supports a family of structurally compatible codes. The interconnect delay and control logic area are reduced by a factor of 2.12 and 8, respectively. Non-binary LDPC codes are effective in combating burst errors. Using the power representation of the elements in the Galois field to organize both intrinsic and extrinsic messages, we present an efficient decoder architecture for non-binary QC-LDPC codes. The proposed decoder is reconfigurable and can be used to decode any code of a given field size. The decoder supports both regular and irregular non-binary QC-LDPC codes. Using a practical metric of throughput per unit area, the proposed implementation outperforms the best implementations published in research literature to date.
Author: Sonali Agarwal
Publisher: Springer Nature
ISBN: 981151366X
Category : Technology & Engineering
Languages : en
Pages : 466
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Book Description
This book features selected high-quality research papers presented at the International Conference on Machine Intelligence and Signal Processing (MISP 2019), held at the Indian Institute of Technology, Allahabad, India, on September 7–10, 2019. The book covers the latest advances in the fields of machine learning, big data analytics, signal processing, computational learning theory, and their real-time applications. The topics covered include support vector machines (SVM) and variants like least-squares SVM (LS-SVM) and twin SVM (TWSVM), extreme learning machine (ELM), artificial neural network (ANN), and other areas in machine learning. Further, it discusses the real-time challenges involved in processing big data and adapting the algorithms dynamically to improve the computational efficiency. Lastly, it describes recent developments in processing signals, for instance, signals generated from IoT devices, smart systems, speech, and videos and addresses biomedical signal processing: electrocardiogram (ECG) and electroencephalogram (EEG).
