Fast Decoding Research Articles

Fast joint source-channel decoding of convolutional coded Markov sequences with Monge property

This work addresses the problem of joint source-channel decoding of a Markov sequence which is first encoded by a source code, then encoded by a convolutional code, and sent through a noisy memoryless channel. It is shown that for Markov sources satisfying the so-called Monge property, both the maximum a posteriori probability (MAP) sequence decoding, as well as the soft output Max-Log-MAP decoding can be accelerated by a factor of K without compromising the optimality, where K is the size of the Markov source alphabet. The key to achieve a higher decoding speed is a convenient organization of computations at the decoder combined with a fast matrix search technique enabled by the Monge property. The same decrease in complexity follows, as a by-product of the development, for the soft output Max-Log-MAP joint source channel decoding in the case when the convolutional coder is absent, result which was not known previously.

Fast coeff_token decoding method and new memory architecture design for an efficient H.264/AVC context-based adaptive variable length coding decoder

A fast coeff_token decoding method based on new memory architecture is proposed to implement an efficient context-based adaptive variable length-coding (CAVLC) decoder. The heavy memory access needed in CAVLC decoding is a significant issue in designing a real system, such as digital multimedia broadcasting players, portable media players, and mobile phones with video, because it results in high power consumption and delay in operations. Recently, a new coeff_token variable-length decoding method has been suggested to achieve memory access reduction. However, it still requires a large portion of the total memory access in CAVLC decoding. In this work, an effective memory architecture is designed through careful examination of codewords in variable-length code tables. In addition, a novel fast decoding method is proposed to further reduce the memory accesses required for reconstructing the coeff_token element. Only one memory access is used for reconstructing each coeff_token element in the proposed method.

Finite Precision Analysis for Space-Time Decoding

Low complexity optimal (or nearly optimal) decoders for space-time codes have recently been under intensive investigation. For example, recent works by Sirianunpiboon and others show that the Silver code and the Golden code can be decoded optimally (or nearly optimally) with quadratic decoding complexity. Fast decodability makes them very attractive in practice. In implementing these decoders, floating-point to fixed-point conversion (FFC) needs to be carefully undertaken to minimize hardware cost while retaining decoding performance. The process of quantization for fixed-point representations is often ignored by research community and lacks investigation, and so FFC is often conducted heuristically based on simulations. This paper studies the effects of quantization to space-time coded systems from an information theoretic perspective. It shows the analytical relationship between quantization error and decoding performance deterioration. This paper also proposes a general finite precision implementation methodology including two FFC criteria for space-time coded systems within an integer optimization framework. As a particular example, this paper examines the finite precision implementation of the quadratic optimal decoding algorithm of the Silver code. However, our methodology and techniques can be applied to general space-time codes.

Design implementation of a quasi-cyclic codec for random access memories on-board Alsat-1

Abstract This paper presents the in-orbit observations of single event upset (SEU) and multiple bit upset (MBU) activity in the commercial random access memories (RAM) onboard the first Algerian microsatellite Alsat-1. The application of the quasi-cyclic codes for double-bit error detection and correction in commercial memories for use onboard Alsat-1 is presented. The performance of the proposed quasi-cyclic codec is measured and compared with two different error detection and correction (EDAC) devices, using the same FPGA technology. It is shown that such a technique is very efficient to detect and correct double bit errors. The results show that a fast and accurate data decoding is achieved and that the algorithm is robust, which makes it applicable in low earth orbits.

An Efficient Low Complexity Lossless Coding Algorithm for Medical Images

Problem statement: Nowadays a large number of various medical images are generated from hospitals and medical centers with sophisticated image acquisition devices, the movement toward digital images in radiology presents the problem of how to conveniently and economically store, retrieve and transmit the volume of digital images. Thus digital image data compression is necessary in order to solve this problem. So in a wide range of medical applications such as disease diagnostic and during the compression process, the loss of information is unacceptable; hence medical images are required to be at high resolution as possible. Instead of lossy compression with relatively high compression ratio, mathematical lossless compression methods are favored in this field. Approach: In this study, an efficient new lossless image coding algorithm using a simple technique was presented. Our coding algorithm was based on pixel redundancy reduction by formulating two matrices only, which were Gray Scale Matrix (GSM) and Binary Matrix (BM). These matrices had been used for coding and decoding processes. Results: Results showed that the maximum compression ratio achieved using the proposed method was 4:1, which was more efficient than the present lossless techniques, moreover the computational complexity is greatly simplified; therefore producing very fast coding and decoding. Conclusion: This algorithm was most suitable for those images where lossy compression was avoided such as medical images used for teleradiology and other telemedicine purposed and it can be applied to other medical modalities.

Fast entropy decoding method for high resolution personal video recorder

In this paper, we propose a fast entropy decoding method that is well suited for personal video recorder (PVR) applications for high resolution video (HRV). In PVR applications supporting HRV, it is essential to implement a fast encoder and decoder due to the large amount of video data. The proposed bit-precision based entropy method (BPEM) provides a way to design a very simple entropy decoding process, which can substantially reduce the overall computational complexity of the decoder. For the purpose of contents protection, it is common to have a proprietary codec in PVR. In such a case, additional transcoding for storing transmitted data is required. However, this may involve a complex process that requires encoding and decoding. The proposed method is only applied to the entropy coding method of the existing standard codecs for transcoding thereby reducing the transcoding complexity down to bitstream-level symbol mapping. We implemented BPEM on an MPEG-4 simple profile (SP) codec. The experimental results showed that BPEM produced about 30 percent lower decoder complexity and 50 to 80 percent lower syntax parsing time while maintaining similar coding efficiency compared to the conventional MPEG-4 SP codec.

Efficient embedded speech recognition for very large vocabulary Mandarin car-navigation systems

Automatic speech recognition (ASR) for a very large vocabulary of isolated words is a difficult task on a resource-limited embedded device. This paper presents a novel fast decoding algorithm for a Mandarin speech recognition system which can simultaneously process hundreds of thousands of items and maintain high recognition accuracy. The proposed algorithm constructs a semi-tree search network based on Mandarin pronunciation rules, to avoid duplicate syllable matching and save redundant memory. Based on a two-stage fixed-width beam-search baseline system, the algorithm employs a variable beam-width pruning strategy and a frame-synchronous word-level pruning strategy to significantly reduce recognition time. This algorithm is aimed at an in-car navigation system in China and simulated on a standard PC workstation. The experimental results show that the proposed method reduces recognition time by nearly 6-fold and memory size nearly 2- fold compared to the baseline system, and causes less than 1% accuracy degradation for a 200,000 word recognition task.

A class of generalized LDPC codes with fast parallel decoding algorithms

Given the Tanner graph of a generalized low-density parity-check (GLDPC) code, the decoding complexity is mainly dominated by the decoding algorithm of subcodes. In this paper, we propose a class of GLDPC codes with fast parallel decoding algorithm. The parity-check matrices of the newly constructed subcodes are composed of several square matrices, which can be viewed as elements of a finite field. Therefore the FFT-based a posteriori probability (APP) algorithm for nonbinary codes can be applied to decode the subcodes. When compared with the trellis-based APP algorithm, the FFT-based APP algorithm can be implemented in parallel and has lower complexity. Simulation results show that the proposed GLDPC codes perform well on AWGN channels.

Timing, Timing, Timing: Fast Decoding of Object Information from Intracranial Field Potentials in Human Visual Cortex

The difficulty of visual recognition stems from the need to achieve high selectivity while maintaining robustness to object transformations within hundreds of milliseconds. Theories of visual recognition differ in whether the neuronal circuits invoke recurrent feedback connections or not. The timing of neurophysiological responses in visual cortex plays a key role in distinguishing between bottom-up and top-down theories. Here, we quantified at millisecond resolution the amount of visual information conveyed by intracranial field potentials from 912 electrodes in 11 human subjects. We could decode object category information from human visual cortex in single trials as early as 100 ms poststimulus. Decoding performance was robust to depth rotation and scale changes. The results suggest that physiological activity in the temporal lobe can account for key properties of visual recognition. The fast decoding in single trials is compatible with feedforward theories and provides strong constraints for computational models of human vision.

DIA: A Complexity-Effective Decoding Architecture

Fast instruction decoding is a true challenge for the design of CISC microprocessors implementing variable-length instructions. A well-known solution to overcome this problem is caching decoded instructions in a hardware buffer. Fetching already decoded instructions avoids the need for decoding them again, improving processor performance. However, introducing such special--purpose storage in the processor design involves an important increase in the fetch architecture complexity. In this paper, we propose a novel decoding architecture that reduces the fetch engine implementation cost. Instead of using a special-purpose hardware buffer, our proposal stores frequently decoded instructions in the memory hierarchy. The address where the decoded instructions are stored is kept in the branch prediction mechanism, enabling it to guide our decoding architecture. This makes it possible for the processor front end to fetch already decoded instructions from the memory instead of the original nondecoded instructions. Our results show that using our decoding architecture, a state-of-the-art superscalar processor achieves competitive performance improvements, while requiring less chip area and energy consumption in the fetch architecture than a hardware code caching mechanism.

Improved parallel weighted bit-flipping decoding algorithm for LDPC codes

Aiming at seeking a low-complexity decoder with fast decoding convergence speed for short or medium low-density parity-check (LDPC) codes, an improved parallel weighted bit-flipping (IPWBF) algorithm, which is applied flexibly for two classes of codes is presented here. For LDPC codes with low column weight in their parity check matrix, both bootstrapping and loop detection procedures, described in the existing literature, are included in IPWBF. Furthermore, a novel delay-handling procedure is introduced to prevent the codeword bits of high reliability from being flipped too hastily. For large column weight finite geometry LDPC codes, only the delay-handling procedure is included in IPWBF to show its effectiveness. Extensive simulation results demonstrate that the proposed algorithm achieves a good tradeoff between performance and complexity.

A low complexity branch-and-bound-based decoder for V-BLAST systems with PSK signals

In this paper, a fast sphere decoder is proposed for the joint detection of phase-shift keying (PSK) signals in uncoded Vertical Bell Laboratories Layered Space Time (V-BLAST) systems. The proposed decoder consists of preprocessing stage and search stage. The preprocessing stage is based on the enhancement of the ordering mean square error decision feedback equalizer (MMSE-DFE). Its role is to generate a tree structure suitable for the search stage. The search stage relies on the depth-first brand-and-bound (BB) algorithm with “best-first” orders stored in lookup tables. Simulation results show that the proposed decoder is able to provide the system with the maximum likelihood (ML) performance at low complexity.

Developmental Links of Very Early Phonological and Language Skills to Second Grade Reading Outcomes

The authors examined second grade reading accuracy and fluency and their associations via letter knowledge to phonological and language predictors assessed at 3.5, 4.5, and 5.5 years in children in the Jyväskylä Longitudinal Study of Dyslexia. Structural equation modeling showed that a developmentally highly stable factor (early phonological and language processing [EPLP]) behind key dyslexia predictors (i.e., phonological awareness, short-term memory, rapid naming, vocabulary, and pseudoword repetition) could already be identified at 3.5 years. EPLP was significantly associated with reading and spelling accuracy and by age with letter knowledge. However, EPLP had only a minor link with reading fluency, which was additionally explained by early letter knowledge. The results show that reading accuracy is well predicted by early phonological and language skills. Variation in fluent reading skills is not well explained by early skills, suggesting factors other than phonological core skills. Future research is suggested to explore the factors behind the development of fast and accurate decoding skills.

Fast decoder for H.264 scalable video coding with selective up-sampling for spatial scalable video coding

Abstract. A simple and effective method is presented forfast decoding of H.264 scalable video coding SVC . Theup-sampling operation in H.264 SVC makes the decodervery complex, because convolution and complex memorytransactions are inevitable. The proposed method exploitscoded modes of neighboring macroblocks MBs for deter-mining up-sampling operation on MB by MB. The experi-mental validation shows considerable improvement in de-coding time, and the proposed method reduces thecomplexity by about 25% on average. © 2008 Society of Photo-Optical Instrumentation Engineers. DOI: 10.1117/1.2957042 Subject terms: video decoder; scalable video coding; upsampling . Paper 080173LR received Mar. 9, 2008; revised manuscriptreceived May 18, 2008; accepted for publication May 20, 2008;published online Jul. 16, 2008. 1 Introduction Although transcoding methods 1–4 support spatial, temporal,and quality adaptation, they require additional tools intransmission. Consequently, a new standard was proposedto provide scalable video models for scalable extension ofH.264/AVC H.264 scalable video coding SVC .

An Alamouti coded OFDM transmission for cooperative systems robust to both timing errors and frequency offsets

In this letter, we propose an Alamouti coded orthogonal frequency-division multiplexing (OFDM) scheme for a cooperative communication system robust to both timing errors and frequency offsets. OFDM with cyclic prefix (CP) is used to combat timing errors. In order to mitigate the intercarrier interference (ICI) caused by multiple frequency offsets in the cooperative system, an ICI-self cancellation scheme is constructed, which can suppress ICI effectively. Moreover, in the proposed scheme, if the channels are real-valued fading channels, the received signals at the destination node have the Alamouti code structure on each subcarrier and thus it has the fast symbol-wise ML decoding and when frequency offsets are not large, the new scheme can achieve diversity order 2.

PAPR Reduction for Repetition Space-Time-Frequency Coded MIMO-OFDM Systems Using Chu Sequences

Space-time/frequency coding (SFC) can achieve the spatial and multipath diversities for a MIMO-OFDM system by coding across subcarriers, multiple antennas, and/or multiple OFDM sysmbols, where an interesting method to achieve the multipath diversity is repeating across subcarriers proposed by Su et al. While most of the existing space-time/frequency codes do not have the fast ML decoding, a family of space-time-frequency codes with single-symbol ML decoding have been proposed lately by Zhang et al to achieve both full spatial and multipath diversities by using orthogonal space-time block codes (OSTBC) across multiple antennas and OFDM symbols and in the meantime repeating across the subcarriers. In this paper, we first generalize the above OSTBC to linearly transformed quasi OSTBC (QOSTBC) in a straightforward way. The main goal of this paper is to modify the repeating process and adjust their phases so that the peak-to-average power ratio (PAPR) of the OFDM system is reduced. In particular, we propose to use Chu sequences and show that the discrete PAPR can be reduced by Gamma times where Gamma is the times of the repeating across subcarriers for any SFC from the repeating.

Quasi-cyclic generalized ldpc codes with low error floors

In this paper, a novel methodology for designing structured generalized low-density parity-check (G-LDPC) codes is presented. The proposed design results in quasi-cyclic G-LDPC codes for which efficient encoding is feasible through shift-register-based circuits. The structure imposed on the bipartite graphs, together with the choice of simple component codes, leads to a class of codes suitable for fast iterative decoding. A pragmatic approach to the construction of G-LDPC codes is proposed. The approach is based on the substitution of check nodes in the protograph of a low-density parity-check code with stronger nodes based, for instance, on Hamming codes. Such a design approach, which we call low-density parity-check (LDPC) code doping, leads to low-rate quasi-cyclic G-LDPC codes with excellent performance in both the error floor and waterfall regions on the additive white Gaussian noise channel.

(23, 12, 7) quadratic residue decoder based on syndrome-weight determination

A novel, fast decoder for the binary quadratic residue code of length 23, or equivalently the famous Golay code is proposed. The core is a new idea to determine the syndrome weight. The decoding algorithm can be implemented with a parallel design, and the decoder based on this algorithm is not only very efficient but also of low area cost. It promises a binary Golay decoder which is faster than available decoders.

Improved low-complexity low-density parity-check decoding

A practical low-complexity decoding of low-density parity-check codes is studied. A fast decoding scheme for weighted bit-flipping (WBF) based algorithms is first proposed. Then, an optimised 2 bit decoding scheme and its VLSI architecture are presented. It is shown that the new approach has significantly better decoding performance while having comparable hardware complexity compared with WBF-based algorithms.

Quasi-Cyclic Generalized LDPC Codes With Low Error Floors

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> In this paper, a novel methodology for designing structured generalized low-density parity-check (G-LDPC) codes is presented. The proposed design results in quasi-cyclic G-LDPC codes for which efficient encoding is feasible through shift-register-based circuits. The structure imposed on the bipartite graphs, together with the choice of simple component codes, leads to a class of codes suitable for fast iterative decoding. A pragmatic approach to the construction of G-LDPC codes is proposed. The approach is based on the substitution of check nodes in the protograph of a low-density parity-check code with stronger nodes based, for instance, on Hamming codes. Such a design approach, which we call low-density parity-check (LDPC) code doping, leads to low-rate quasi-cyclic G-LDPC codes with excellent performance in both the error floor and waterfall regions on the additive white Gaussian noise channel. </para>