Fast Decoding Research Articles

Design of the Recognition and Decoding System of PDF417 Barcode Based on LabVIEW

The symbol structure of PDF417 barcode was introduced in detail, and a recognition and decoding system of PDF417 barcode based on software development platform of the LabVIEW virtual instrument was designed and implemented. The system can process and analyze the images containing PDF417 barcode collected by camera in real time, achieve the fast and omnibearing decoding of the barcode.

적응적 탐색 영역을 이용한 보조 정보 생성의 고속화 방법

분산 비디오 압축(DVC, Distributed Video Coding) 기술은 부호화기의 움직임 추정과 같은 복잡한 과정을 복호화기로 이동시킴으로써 경량화 비디오 부호화를 가능하게 하는 새로운 방법으로 주목 받고 있다. 한편, DVC 복호화기에서는 움직임 추정과 보상 과정뿐만 아니라 채널 복호 과정도 수행해야 하기 때문에 복호화기의 복잡도는 크게 증가하게 된다. 이에 복호화기 복잡도의 가장 많은 비중을 차지하는 채널 복호 과정을 고속화하기 위한 다양한 방법이 제안되고 있다. 하지만 다양한 고속화 방법에 의해 채널 복호 과정이 고속화될수록 채널 복호화 이외의 과정들에 대한 복잡도가 부각되는데, 일례로 DVC 복호화기에서 낮은 비율을 차지하던 보조 정보생성 과정의 복잡도가 상대적으로 증가된다. 따라서 본 논문에서는 보조 정보 생성 과정에 적응적 탐색 영역 방법을 적용하여 DVC 복호 과정을 고속화할 수 있는 알고리즘을 제안한다. 제안된 적응적 탐색 영역을 이용하는 방법을 적용할 경우 고정된 탐색 영역을 적용한 종래의 방법에 비해 평균적으로 보조 정보 생성 시간의 63% 정도가 절감 가능하며, 저하되는 율 왜곡 성능은 약 0.17%(BDBR) 정도로 상당히 낮다. In Distributed Video Coding(DVC), a low complexity encoder can be realized by shifting complex processes of encoder such as motion estimation to decoder. Since not only motion estimation/compensation processes but also channel decoding process needs to be performed at DVC decoder, the complexity of a decoder is significantly increased in consequence. Therefore, various fast channel decoding methods are proposed for the most computationally complex part, which is the channel decoding process in DVC decoding. As the channel decoding process becomes faster using various methods, however, the complexity of the other processes are relatively highlighted. For instance, the complexity of side information generation process in the DVC decoder is relatively increased. In this paper, therefore, a fast method for the DVC decoding is proposed by using adaptive search range method in side information generation process. Experimental results show that the proposed method achieves time saving of about 63% in side information generation process, while its rate distortion performance is degraded only by about 0.17% in BDBR.

Study on Quasi-Orthogonal Space Time Block Code Based on Amplify-and-Forward Relay Networks

A kind of quasi-orthogonal space time block code for amplify-and-forward relay networks is analyzed in this paper. At the source, 4 single-antenna users transmit the quasi-orthogonal space time block code matrix. At the relay node, fast maximum-likelihood decoding algorithm is adopted and the decoded symbols are then encoded into quasi-orthogonal code which is transmitted through transmit antenna. At the destination, pair-wise decoding algorithm is utilized. Finally we compare the performance of the quasi-orthogonal space time block code in relay networks with that of the quasi-orthogonal space time block code in traditional communication system. Simulation results show that at the given BER of 10-3, the new code can provide about gain of 4dB and 1 dB comparing with that for the traditional quasi-orthogonal code, respectively. And at the given BER of 10-5, the new code can provide about gain of 4.6dB and 2.6dB comparing with that for the old quasi-orthogonal code, respectively.

Fast Decoding and Hardware Design for Binary-Input Compressive Sensing

Binary-input compressive sensing (BiCS) has recently been applied to wireless communications as a modulated coding scheme for seamless rate adaptation. Different from conventional channel codes which generate binary symbols with logical-OR (XOR) operations, BiCS generates multilevel symbols through weighted sum operation. Although BiCS can be decoded by message passing, it needs to compute the convolution of probability functions in each iteration. The high decoding complexity has prevented the technique from being applied to practical use. In this paper, we propose a fast BiCS decoding algorithm and its corresponding partial-parallel hardware design. In this algorithm, we first build lookup tables to solve the computationally intensive problem of convolution. Through these tables, we successfully convert the convolution of probabilities into the polynomial of some exponential terms. This key step allows us to use log-likelihood ratio as message in message passing decoding and a fast algorithm is developed by approximate computing. We further design a partial-parallel hardware decoder. To avoid memory collision, we propose a multilevel cyclic-shift approach to generate the CS measurement matrix. We design horizontal unit processors with the proposed tables for iterative computing. Our analyses show that the proposed fast algorithm can reduce multiplications by nearly 90%. The decoding speed of our field-programmable gate array design reaches the range of communication rate in modern wireless networks.

Joint Source-Channel Decoding Over MIMO Channels Based on Partial Marginalization

We investigate fast joint source-channel decoding employed for communication over frequency-flat and frequency-selective block-fading multiple-input multiple-output channels. Our setting has applications for communication with short codes under low-latency constraints. The case of no transmitter channel state information is considered. We propose a partial marginalization decoder that allows performance to be traded for computational complexity, by adjusting a user parameter. By tuning this parameter to its maximum value, the minimum mean square error (MMSE) decoder is obtained. In the conducted simulations, the proposed scheme almost achieves the MMSE performance for a wide range of the channel signal-to-noise ratios, with significant reductions in computational complexity.

Algebraic decoding of the (73, 37, 13) quadratic residue code

In this study, an efficient and fast algebraic decoding algorithm (ADA) for the binary systematic quadratic residue (QR) code of length 73 with the reducible generator polynomial to correct up to six errors is proposed. The S(I, J) matrix method given by He et al. (2001) is utilised to compute the unknown syndromes S5. A technique called swap base is proposed to correct the weight-4 error patterns. To correct the weight-5 error patterns, the new error-locator polynomials for decoding the five errors are derived. Finally, the modified shift-search algorithm (SSA) developed by Lin et al. (2010) is applied to correct the weight-6 error patterns. Moreover, the computations of all syndromes are achieved in a small finite field. Simulation results show that the proposed ADA is practical.

Quasi Orthogonal Space Time Block Codes Using Various Sub-Block Matrices

Space-time block codes (STBCs) from Orthogonal designs have attracted attention due to their fast maximum likelihood decoding and full diversity, but the maximum symbol transmission rate for complex signals is only ¾ for four transmit antennas so quasi orthogonal STBC was proposed, in this paper the structure and characteristics of some new type of a Quasi-orthogonal space time block codes (QOSTBC)is analyzed, The error performance for these codes for four transmitted antennas over uncorrelated and spatially correlated MIMO channels is investigated. A maximum likelihood (ML) decoding algorithm for the suggested code is also provided.

Improving Parse Trees for Efficient Variable-to-Fixed Length Codes

We address the problem of improving variable-length-to-fixed-length codes (VF codes). A VF code that we deal here with is an encoding scheme that parses an input text into variable length substrings and then assigns a fixed length codeword to each parsed substring. VF codes have favourable properties for fast decoding and fast compressed pattern matching, but they are worse in compression ratio than the latest compression methods. The compression ratio of a VF code depends on the parse tree used as a dictionary. To gain a better compression ratio we present several improvement methods for constructing parse trees. All of them are heuristical solutions since it is intractable to construct the optimal parse tree. We compared our methods with the previous VF codes, and showed experimentally that their compression ratios reach to the level of state-of-the-art compression methods.

A fast progressive image transmission scheme using block truncation coding by pattern fitting

In this paper, we have proposed a novel progressive image transmission scheme. In the present method, the concept of the BTC-PF is used for faster decoding. Here, images are decomposed into a number of blocks based on smoothness criterion. The smooth blocks are encoded by block means and the others are by BTC-PF method. To encode a block by BTC-PF method, the codebook is organized like a full search progressive transmission tree which helps greatly in efficient progressive transmission. The present method provides good image quality at low bit-rate and faster decoding compared to other spatial domain progressive transmission methods. We extend this method for color images also. In color image coding, each color plane is encoded separately and then the encoded information of the planes are transmitted in interleaving manner to obtain color images right from the early stages.

A BP Decoding Algorithm Based on Nodes Residual for LDPC Codes and its Hardware Implementation

We researched BP decoding algorithm based on variable-to-check information residual for LDPC code (VC-RBP) in this paper. It is a dynamic scheduling belief propagation using residuals, and has some advantages，such as fast decoding, good performance, and low complexity. It is similar to residual belief propagation (RBP),but has some difference in computing the residual message. This paper further optimized the new algorithm on DSP of TMS320dm6446, and it is good for hardware implementation.

A fast VQ codebook search with initialization and search order

Vector quantization (VQ), a lossy image compression, is widely used for many applications due to its simple architecture, fast decoding ability, and high compression rate. Traditionally, VQ applies the full search algorithm to search for the codeword that best matches each image vector in the encoding procedure. However, matching in this manner consumes a lot of computation time and leads to a heavy burden for the VQ method. Therefore, Torres and Huguet proposed a double test algorithm to improve the matching efficiency. However, their scheme does not include an initiation strategy to choose an initially searched codeword for each image vector, and, as a result, matching efficiency may be affected significantly. To overcome this drawback, we propose an improved double test scheme with a fine initialization as well as a suitable search order. Our experimental results indicate that the computation time of the double test algorithm can be significantly reduced by the proposed method. In addition, the proposed method is more flexible than existing schemes.

Extensions of Compressed Imaging: Flying Sensor, Coded Mask, and Fast Decoding

In this paper, we outline some recent advances and identify some open problems in compressed sensing (CS) for remote imaging and related imaging applications. We propose new approaches to compressed remote sensing and image reconstruction, which exploit redundant/overlapping measurements (RMs), multiplexing imaging (MI), and an effective iterative procedure for decoding in the recovery phase. The RM approach involves the concept of data fusion and applies a noiselet transform to a CS measurement matrix, followed by 2-D hexagonal jittered sampling and 1-D jitter-based circular sampling. The MI approach enlarges the field of regard of imaging and provides the compromise between the numbers of masks and detectors by taking advantage of the merits of previous single-pixel sequent imaging and multipixel parallel imaging. Finally, the new decoding method in the CS recovery stage combines Bregman-based nonlocal total variation with curvelet-active-set iteration.

Efficient Implementation of Linear Programming Decoding

While linear programming (LP) decoding provides more flexibility for finite-length performance analysis than iterative message-passing (IMP) decoding, it is computationally more complex to implement in its original form, due to both the large size of the relaxed LP problem and the inefficiency of using general-purpose LP solvers. This paper explores ideas for fast LP decoding of low-density parity-check (LDPC) codes. By modifying the previously reported Adaptive LP decoding scheme to allow removal of unnecessary constraints, we first prove that LP decoding can be performed by solving a number of LP problems that each contains at most one linear constraint derived from each of the parity-check constraints. By exploiting this property, we study a sparse interior-point implementation for solving this sequence of linear programs. Since the most complex part of each iteration of the interior-point algorithm is the solution of a (usually ill-conditioned) system of linear equations for finding the step direction, we propose a preconditioning algorithm to facilitate solving such systems iteratively. The proposed preconditioning algorithm is similar to the encoding procedure of LDPC codes, and we demonstrate its effectiveness via both analytical methods and computer simulation results.

A novel architecture for fast 2D IDCT decoders, with reduced number of multiplications

This paper presents a new architecture for the fast computation of the 8×8 two dimensional (2D) Inverse Discrete Cosine Transform (IDCT). The key idea of the proposed method is the permanent storage of the Basis Matrices of the 8×8 2D Discrete Cosine Transform (DCT). By exploiting the sparseness property of the 2D DCT coefficient matrix, the computational time decreases as the number of nonzero coefficients decreases. Moreover, by exploiting the symmetry properties inherent in the Basis Matrices, the introduced method reduces the number of multipliers as well as the number of required multiplications. The proposed structure computes all 64 pixel luminance values of an 8×8 block simultaneously. The efficiency of the proposed architecture is validated through simulations.

Improved multi-pass fast correlation attacks with applications

In this paper we propose two new algorithms for multi-pass fast correlation attacks on stream ciphers. The first algorithm aims at fast symbol-wise decoding in the circumstances that the noise is not very high and we have little resource for pre-computation. The second algorithm deals with the practical decoding problem in the high noise and limited keystream cases. The new algorithms are applicable to arbitrary form LFSR and compare favorably to the previously known algorithms in the scenarios under consideration. As applications, we demonstrate new key recovery attacks on one-level Bluetooth E0 and LILI-128, respectively. Given 237-bit keystream and 228-byte memory, our attack against one-level E0 needs 235.1 operations. Given 224-bit keystream and 224.5-byte memory, our attack on LILI-128 has time complexity 270.6 operations.

Fast decoding of the (23, 12, 7) Golay code with four‐error‐correcting capability

ABSTRACTIn this paper, a fast and efficient decoding algorithm for correcting the (23, 12, 7) Golay code up to four errors is presented. The aim of this paper is to develop a fast syndrome‐group search method for finding the candidate codewords by utilizing the property that the syndromes of the weight‐4 error patterns are identical to that of the weight‐3 error pattern. When the set of the candidate codewords is constructed, the most likely one is determined by assessing the corresponding correlation metrics. The well‐known Chase‐II decoder, which needs to perform the hard‐decision decoder multiple times, acts as a comparison basis. Simulation results over the additive white Gaussian noise channel show that the decoding complexity of the proposed method is averagely reduced by at least 86% in terms of the decoding time. Furthermore, the successful decoding percentage of the new decoder in the case of four errors is always superior to Chase‐II decoder. At the signal‐to‐noise ratio of 0 dB, the proposed algorithm still can correct up to 97.40% weight‐4 error patterns. The overall bit error rate performance of the proposed decoder is close to that of Chase‐II decoder. It implies that the new decoder is beneficial to the practical implementation. Copyright © 2011 John Wiley & Sons, Ltd.

Fast decoding algorithms for variable-lengths codes

Data compression has been widely applied in many data processing areas. Compression methods use variable-length codes with the shorter codes assigned to symbols or groups of symbols that appear in the data frequently. There exist many coding algorithms, e.g. Elias-delta codes, Fibonacci codes and other variable-length codes which are often applied to encoding of numbers. Although we often do not consider time consumption of decompression as well as compression algorithms, there are cases where the decompression time is a critical issue. For example, a real-time compression of data structures, applied in the case of the physical implementation of database management systems, follows this issue. In this case, pages of a data structure are decompressed during every reading from a secondary storage into the main memory or items of a page are decompressed during every access to the page. Obviously, efficiency of a decompression algorithm is extremely important. Since fast decoding algorithms were not known until recently, variable-length codes have not been used in the data processing area. In this article, we introduce fast decoding algorithms for Elias-delta, Fibonacci of order 2 as well as Fibonacci of order 3 codes. We provide a theoretical background making these fast algorithms possible. Moreover, we introduce a new code, called the Elias–Fibonacci code, with a lower compression ratio than the Fibonacci of order 3 code for lower numbers; however, this new code provides a faster decoding time than other tested codes. Codes of Elias–Fibonacci are shorter than other compared codes for numbers longer than 26 bits. All these algorithms are suitable in the case of data processing tasks with special emphasis on the decompression time.

Two Relay Strategies in Multi-Node Cooperative Communications in Ad-Hoc Networks

In this patent, we propose and compare two different relaying strategies in cooperative communications involving channel coding, network coding and turbo decoding in a wireless Ad-Hoc network scenario. A wireless Ad-Hoc Network is a decentralized network where each node can join the cooperative communication as a relay by decoding and forwarding data from other nodes to the destination. In this work multiple nodes send data to the destination with the assistance of a single relay node where the decode-and-forward (DF) protocol is adopted. One relay strategy uses network coding after the relay successfully receives and decodes information frames from all source nodes. The other strategy uses recursive systematic convolutional (RSC) channel coding at the relay for the interleaved, decoded information steams from all source nodes. At the destination, turbo decoding is carried out for both schemes. We show through simulations that both methods have a fast turbo decoding convergence within two or three iterations. The second one provides a better performance when the signal-to-noise ratio in the relay link is relatively high. However, in the case where the relay link is weak, the first one with network coding outperforms. This result indicates that different channel conditions require different relaying strategies and a proper switch between strategies in the relay may improve the overall performance of Ad-Hoc networks.

A Future Simplification of Procedure for Decoding Nonsystematic Reed-Solomon Codes Using the Berlekamp-Massey Algorithm

It is well-known that the Euclidean algorithm can be used o find the systematic errata-locator polynomial and the errata-evaluator polynomial simultaneously in Berlekamp's key equation that is needed to decode a Reed-Solomon (RS) codes. In this paper, a simplified decoding algorithm to correct both errors and erasures is used in conjunction with the Euclidean algorithm for efficiently decoding nonsystematic RS codes. In fact, this decoding algorithm is an appropriate modification to the algorithm developed by Shiozaki and Gao. Based on the ideas presented above, a fast algorithm described from Blahut's classic book is derivated and proved in this paper to correct erasures as well as errors by replacing the Euclidean algorithm by the Berlekamp-Massey (BM) algorithm. These facts lead to significantly reduce the decoding complexity of the proposed RS decoder. In addition, computer simulations show that this simple and fast decoding technique reduces the decoding time when compared with existing efficient algorithms including the new Euclidean-algorithm-based decoding approach proposed in this paper.

On improving Tunstall codes

Though many compression methods are based on the use of variable length codes, there has recently been a trend to search for alternatives in which the lengths of the codewords are more restricted, which can have useful applications, such as easier processing and fast decoding. This paper explores the construction of variable-to-fixed length codes, which have been suggested long ago by Tunstall. Using new heuristics based on suffix trees, the performance of Tunstall codes can in some cases be improved by more than 40%.