21 research outputs found

    Characterization and Efficient Search of Non-Elementary Trapping Sets of LDPC Codes with Applications to Stopping Sets

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    In this paper, we propose a characterization for non-elementary trapping sets (NETSs) of low-density parity-check (LDPC) codes. The characterization is based on viewing a NETS as a hierarchy of embedded graphs starting from an ETS. The characterization corresponds to an efficient search algorithm that under certain conditions is exhaustive. As an application of the proposed characterization/search, we obtain lower and upper bounds on the stopping distance smins_{min} of LDPC codes. We examine a large number of regular and irregular LDPC codes, and demonstrate the efficiency and versatility of our technique in finding lower and upper bounds on, and in many cases the exact value of, smins_{min}. Finding smins_{min}, or establishing search-based lower or upper bounds, for many of the examined codes are out of the reach of any existing algorithm

    Lowering the Error Floor of LDPC Codes Using Cyclic Liftings

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    Cyclic liftings are proposed to lower the error floor of low-density parity-check (LDPC) codes. The liftings are designed to eliminate dominant trapping sets of the base code by removing the short cycles which form the trapping sets. We derive a necessary and sufficient condition for the cyclic permutations assigned to the edges of a cycle cc of length â„“(c)\ell(c) in the base graph such that the inverse image of cc in the lifted graph consists of only cycles of length strictly larger than â„“(c)\ell(c). The proposed method is universal in the sense that it can be applied to any LDPC code over any channel and for any iterative decoding algorithm. It also preserves important properties of the base code such as degree distributions, encoder and decoder structure, and in some cases, the code rate. The proposed method is applied to both structured and random codes over the binary symmetric channel (BSC). The error floor improves consistently by increasing the lifting degree, and the results show significant improvements in the error floor compared to the base code, a random code of the same degree distribution and block length, and a random lifting of the same degree. Similar improvements are also observed when the codes designed for the BSC are applied to the additive white Gaussian noise (AWGN) channel

    On The Error-Prone Substructures for The Binary-Input Ternary-Output Channel and Its Corresponding Exhaustive Search Algorithm

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    Abstract-The error floor performance of a low-density paritycheck (LDPC) code is highly related to the presence of errorprone substructures (EPSs). In general, existing characterizations of the EPSs are inspired by the LDPC decoding behavior under simple binary erasure channel (BEC) and binary symmetric channel (BSC) models. In this work, we first introduce a new class of EPSs: the 1-shot EPSs and static EPSs for the binaryinput ternary-output channel (BITOC). By focusing on BITOCs, which are a step closer to additive white Gaussian channels (AWGNC), the proposed EPS would better characterize the decoding behavior of the AWGNC than the existing BECor BSC-based definitions. We then develop an efficient search algorithm that can exhaustively enumerate all small BITOC EPSs. The new exhaustive algorithm enables us to order the harmfulness of the EPSs and distinguish within a given EPS which bits are more prone to what types of errors. The proposed algorithm can also be regarded as a unified search method for the existing EPSs such as cycles, codewords, stopping sets, and fully absorbing sets. The proposed methodology is potentially generalizable to the binary-input m-ary output channel

    An Efficient Algorithm for Finding Dominant Trapping Sets of LDPC Codes

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    This paper presents an efficient algorithm for finding the dominant trapping sets of a low-density parity-check (LDPC) code. The algorithm can be used to estimate the error floor of LDPC codes or to be part of the apparatus to design LDPC codes with low error floors. For regular codes, the algorithm is initiated with a set of short cycles as the input. For irregular codes, in addition to short cycles, variable nodes with low degree and cycles with low approximate cycle extrinsic message degree (ACE) are also used as the initial inputs. The initial inputs are then expanded recursively to dominant trapping sets of increasing size. At the core of the algorithm lies the analysis of the graphical structure of dominant trapping sets and the relationship of such structures to short cycles, low-degree variable nodes and cycles with low ACE. The algorithm is universal in the sense that it can be used for an arbitrary graph and that it can be tailored to find other graphical objects, such as absorbing sets and Zyablov-Pinsker (ZP) trapping sets, known to dominate the performance of LDPC codes in the error floor region over different channels and for different iterative decoding algorithms. Simulation results on several LDPC codes demonstrate the accuracy and efficiency of the proposed algorithm. In particular, the algorithm is significantly faster than the existing search algorithms for dominant trapping sets

    Broadcast Coded Slotted ALOHA: A Finite Frame Length Analysis

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    We propose an uncoordinated medium access control (MAC) protocol, called all-to-all broadcast coded slotted ALOHA (B-CSA) for reliable all-to-all broadcast with strict latency constraints. In B-CSA, each user acts as both transmitter and receiver in a half-duplex mode. The half-duplex mode gives rise to a double unequal error protection (DUEP) phenomenon: the more a user repeats its packet, the higher the probability that this packet is decoded by other users, but the lower the probability for this user to decode packets from others. We analyze the performance of B-CSA over the packet erasure channel for a finite frame length. In particular, we provide a general analysis of stopping sets for B-CSA and derive an analytical approximation of the performance in the error floor (EF) region, which captures the DUEP feature of B-CSA. Simulation results reveal that the proposed approximation predicts very well the performance of B-CSA in the EF region. Finally, we consider the application of B-CSA to vehicular communications and compare its performance with that of carrier sense multiple access (CSMA), the current MAC protocol in vehicular networks. The results show that B-CSA is able to support a much larger number of users than CSMA with the same reliability.Comment: arXiv admin note: text overlap with arXiv:1501.0338

    Reliable chip design from low powered unreliable components

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    The pace of technological improvement of the semiconductor market is driven by Moore’s Law, enabling chip transistor density to double every two years. The transistors would continue to decline in cost and size but increase in power. The continuous transistor scaling and extremely lower power constraints in modern Very Large Scale Integrated(VLSI) chips can potentially supersede the benefits of the technology shrinking due to reliability issues. As VLSI technology scales into nanoscale regime, fundamental physical limits are approached, and higher levels of variability, performance degradation, and higher rates of manufacturing defects are experienced. Soft errors, which traditionally affected only the memories, are now also resulting in logic circuit reliability degradation. A solution to these limitations is to integrate reliability assessment techniques into the Integrated Circuit(IC) design flow. This thesis investigates four aspects of reliability driven circuit design: a)Reliability estimation; b) Reliability optimization; c) Fault-tolerant techniques, and d) Delay degradation analysis. To guide the reliability driven synthesis and optimization of combinational circuits, highly accurate probability based reliability estimation methodology christened Conditional Probabilistic Error Propagation(CPEP) algorithm is developed to compute the impact of gate failures on the circuit output. CPEP guides the proposed rewriting based logic optimization algorithm employing local transformations. The main idea behind this methodology is to replace parts of the circuit with functionally equivalent but more reliable counterparts chosen from a precomputed subset of Negation-Permutation-Negation(NPN) classes of 4-variable functions. Cut enumeration and Boolean matching driven by reliability-aware optimization algorithm are used to identify the best possible replacement candidates. Experiments on a set of MCNC benchmark circuits and 8051 functional microcontroller units indicate that the proposed framework can achieve up to 75% reduction of output error probability. On average, about 14% SER reduction is obtained at the expense of very low area overhead of 6.57% that results in 13.52% higher power consumption. The next contribution of the research describes a novel methodology to design fault tolerant circuitry by employing the error correction codes known as Codeword Prediction Encoder(CPE). Traditional fault tolerant techniques analyze the circuit reliability issue from a static point of view neglecting the dynamic errors. In the context of communication and storage, the study of novel methods for reliable data transmission under unreliable hardware is an increasing priority. The idea of CPE is adapted from the field of forward error correction for telecommunications focusing on both encoding aspects and error correction capabilities. The proposed Augmented Encoding solution consists of computing an augmented codeword that contains both the codeword to be transmitted on the channel and extra parity bits. A Computer Aided Development(CAD) framework known as CPE simulator is developed providing a unified platform that comprises a novel encoder and fault tolerant LDPC decoders. Experiments on a set of encoders with different coding rates and different decoders indicate that the proposed framework can correct all errors under specific scenarios. On average, about 1000 times improvement in Soft Error Rate(SER) reduction is achieved. Last part of the research is the Inverse Gaussian Distribution(IGD) based delay model applicable to both combinational and sequential elements for sub-powered circuits. The Probability Density Function(PDF) based delay model accurately captures the delay behavior of all the basic gates in the library database. The IGD model employs these necessary parameters, and the delay estimation accuracy is demonstrated by evaluating multiple circuits. Experiments results indicate that the IGD based approach provides a high matching against HSPICE Monte Carlo simulation results, with an average error less than 1.9% and 1.2% for the 8-bit Ripple Carry Adder(RCA), and 8-bit De-Multiplexer(DEMUX) and Multiplexer(MUX) respectively
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