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About 284 papers for “BCJR algorithm”
Ling Li · 2001
For the BCJR algorithm, a conjecture is that the p.d.f. of the log-likelihood ratio (LLR) is gaussian with variance twice as the expectation. My experiments showed that this conjecture is not true.
Cited by 0
Florin Lucian Morgoș · SHILAP Revista de lepidopterología · 2013
In this paper I will present some concepts related to turbo codes, the principle of their operation, and some results obtained by implementing the BCJR decoding algorithm known as the maximum aposteriori algorithm (MAP).
Cited by 0Open access
Dario Fertonani, Alan Barbieri, Giulio Colavolpe · IEEE Transactions on Communications · 2007
We propose novel techniques to reduce the complexity of the well-known Bahl, Cocke, Jelinek, and Raviv (BCJR) algorithm when it is employed as a detection algorithm in turbo equalization schemes. In particular, by also considering an alternative formulation of the BCJR algorithm, which is more suitable than the original one for deriving reduced-complexity techniques, we describe three reduced-complexity algorithms, each of them particularly effective over one of the three different classes of channels affected by intersymbol interference (minimum-phase, maximum-phase, and mixed-phase channels). The proposed algorithms do not explore all paths on the trellis describing the channel memory, but they work only on the most promising ones, chosen according to the maximum a posteriori criterion. Moreover, some optimization techniques improving the effectiveness of the proposed solutions are described. Finally, we report the results of computer simulations showing the impressive performance of the proposed algorithms, and we compare them with other solutions in the literature.
Cited by 72
Dario Fertonani, Alan Barbieri, Giulio Colavolpe · IEEE Transactions on Communications · 2007
<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> We propose novel techniques to reduce the complexity of the well-known Bahl–Cocke–Jelinek–Raviv (BCJR) algorithm when it is employed as a detection algorithm in turbo equalization schemes. In particular, by also considering an alternative formulation of the BCJR algorithm, which is more suitable than the original for deriving reduced-complexity techniques, we describe three reduced-complexity algorithms, each of them being particularly effective over one of the three different classes of channels (minimum-phase, maximum-phase, and mixed-phase channels) affected by intersymbol interference. The proposed algorithms do not explore all paths on the trellis describing the channel memory, but they work only on the most promising ones, which are chosen according to the maximum <emphasis emphasistype="italic">a posteriori</emphasis> criterion. Moreover, some optimization techniques for improving the effectiveness of the proposed solutions are described. Finally, we report the results of computer simulations showing the impressive performance of the proposed algorithms, and compare them with other solutions in the literature. </para>
Cited by 3
Murat H. Sazlı, Can Işık · Digital Signal Processing · 2006
Cited by 10
M. Moerz, J. Hagenauer, E. Offer · 2002
Fundamental building blocks for analog decoders are introduced which transform log-likelihood ratios into probabilities and vice versa. By interconnecting these blocks general trellis modules can be designed for an analog VLSI implementation of the APP (BCJR) decoding algorithm.
Cited by 8
Christina Fragouli, N. Seshadri, William Turin · Wireless Communications and Mobile Computing · 2001
Abstract The complexity of channel equalization using the BCJR algorithm [Bahl LR et al. IEEE Transactions on Info. Theory 1974; 20 : 284–287] grows exponentially with the channel memory. The M‐BCJR algorithm [Franz V, Anderson J. IEEE J. Selected Areas Comm . 1998; 16 (2): 186–195] provides a method for reduced‐trellis channel equalization, but its performance varies significantly with the distribution of a channel energy to its taps. This paper proposes a variation of the M‐algorithm, based on the implementation of the BCJR algorithm in the logarithmic domain, which can offer robust performance. Designer choices such as the decision delay, maximum and minimum phase transformation, and selection of states are discussed. Simulation results demonstrate the effect of different parameters on the proposed algorithm's performance. Copyright © 2001 John Wiley & Sons, Ltd.
Cited by 5Open access
John B. Anderson, Tomas Eriksson, Norbert Goertz · IEEE Transactions on Information Theory · 2007
The Bahl-Cocke-Jelinek-Raviv (BCJR) algorithm is an important channel decoding method. We extend it to trellis rate-distortion data compression. Beginning from source coding principles, the derivation of the algorithm avoids channel coding or soft output ideas. The encoder does not use entropy coding; equiprobable reproducer letters are emphasized since these maximize entropy. The BCJR method is demonstrated by tests of a tail-biting variant. It performs much better than the ordinary Viterbi algorithm for short and medium blocks. However, the improvement stems from tail biting; the role of the BCJR is to achieve tail biting in a relatively simple way. Some issues that arise with tail biting are explored. It is shown that there is an optimal trellis state size for each block length.
Cited by 2
Jacob H. Gunther, Debora Keller, Todd K. Moon · 2006
A generalization of the BCJR algorithm is derived to compute joint posterior probabilities of arbitrary sets of symbols given received data. A special case of the new algorithm that computes pairwise joint probabilities is used to evaluate the second order statistics needed for EM estimation of carrier phase and symbol timing offsets in a digitally modulated waveform. This EM estimator is integrated into a turbo synchronization loop in which soft information is exchanged between the generalized BCJR algorithm (the synchronizer) and an LDPC decoder.
Cited by 6
Shpylka, O. O., Jurkov, I. O., Zhuk, S. Ya. · Bulletin Of The NTUU "KPI". Series Radiotechnics, Radio Apparatus Building (National Technical University of Ukraine) · 2010
Cited by 0Open access
Alexey A. Bandyukov, Andrey A. Metlyakov, Fedor Ivanov · 2025
Generalized low-density parity-check (GLDPC) codes have emerged as a promising class of error-correcting codes that extend the capabilities of traditional LDPC codes by incorporating more powerful component codes. This paper investigates an approach to construct long GLDPC codes using short component codes. In this scheme, the BCJR algorithm is used as a component decoder and integrated into the belief propagation algorithm. Simulation results demonstrate that constructions incorporating quasi-cyclic LDPC codes yield the best performance. Compared to the conventional decoding approach for LDPC codes, the proposed generalized constructions demonstrated better bit and frame error rate performance. This approach is promising for communication systems that require low latency. A comparison is also provided with LDPC codes constructed using the Progressive Edge-Growth (PEG) algorithm.
Cited by 0
Terje Normann Olsen · Duo Research Archive (University of Oslo) · 2007
The introduction of turbo codes in 1993 was a breakthrough in constructing error correction codes that were able to approach the theoretical limit of performance. Different implementations of turbo codes have become widely used in recent wireless communication systems. \nIt is possible for hardware manufacturers to buy complete turbo decoding solutions as integrated circuits or IP (Intellectual Property) blocks, but these are usually tailor-made for a specific application. \nThis thesis presents a parameterized hardware implementation of the turbo decoding algorithm, called a SISO module, that is generic (parameterized behavior and structure) and scalable. Thus, for each application a balanced decision can be made taking into consideration speed, complexity and power consumption. The proposed implementation can be used as a constituent decoder in parallel or serial turbo decoding networks, in a turbo equalizer or as a MAP decoder.\nA performance loss less than 0.08dB was accomplished for the fixed point implementation with short bit widths by an exploration of performance for different representation of external and internal signals and eliminating destructive saturation.\nAn effort was made in exploring and combining the latest research available to reduce complexity and the signal path.\nThe signal path through the decoder was shortened by implementing parallel circuits for all arithmetic operations of the algorithm, and simplifying or eliminating logic. The throughput for a turbo decoder based on the SISO IP was shown to be comparable to other recent implementations. \nThe thesis work includes developing and optimizing a behavior model in ANSI C/ MATLAB, implementing the module in VHDL, testing, and synthesizing for ASIC and FPGA.
Cited by 0Open access
Aditya Nori, Priti Shankar · 2003
WE describe two constructions for tail-biting trellises that are very similar to the well known BCJR construction for conventional trellises. The constructions lead to a simple proof of the fact that there exist linear tail-biting trellises for a linear code and its dual, which have the same state-complexity profiles.
Cited by 1
Chien‐Ming Wu, Ming‐Der Shieh, Chien-Hsing Wu · 2003
Turbo coding is a powerful encoding and decoding technique that can provide highly reliable data transmission at extremely low signal-to-noise ratios. According to the computational complexity of the employed decoding algorithm, the realization of turbo decoders usually takes a large amount of memory spaces and potentially long decoding delay. Therefore, an efficient memory management strategy becomes one of the key factors toward successfully designing turbo decoders. This paper focuses on the development of general formulas for efficient memory management of turbo decoders employing the sliding-window BCJR algorithm. Three simple but general results are presented to evaluate the required memory size, throughput rate, and latency based on the speed and the number of adopted processors. The results thus provide useful and general information on practical implementations of turbo decoders.
Cited by 7
Bartosz Mielczarek, Arne Svensson · 2001
The classical method for decoding of turbo codes is the BCJR algorithm with perfect channel knowledge and synchronization assumption. The statistics of soft bits produced by the BCJR algorithm change significantly when synchronization is not ideal. Hence, soft bits can be used in post-processing to improve classical synchronization algorithms. This paper discusses the soft bit behavior when the received signal is suffering from a timing offset. The influence of synchronization parameter offset is modeled as increased pseudoGaussian noise power, which has been shown to provide results well agreeing with simulations. The modified signal parameters are then used to approximate the mean behavior of the soft bit output for the first iteration. Finally, a simple synchronizer using the derived soft bit properties is shown to outperform the classical ML synchronizer. Keywords: Turbo codes, timing offset, AWGN channel, BCJR algorithm.
Cited by 0
Christina Fragouli, Nambirajan Seshadri, William Turin · Infoscience (Ecole Polytechnique Fédérale de Lausanne) · 2006
Abstract The complexity of channel equalization using the BCJR algorithm [Bahl LR et al. IEEE Transactions on Info. Theory 1974; 20 : 284–287] grows exponentially with the channel memory. The M‐BCJR algorithm [Franz V, Anderson J. IEEE J. Selected Areas Comm . 1998; 16 (2): 186–195] provides a method for reduced‐trellis channel equalization, but its performance varies significantly with the distribution of a channel energy to its taps. This paper proposes a variation of the M‐algorithm, based on the implementation of the BCJR algorithm in the logarithmic domain, which can offer robust performance. Designer choices such as the decision delay, maximum and minimum phase transformation, and selection of states are discussed. Simulation results demonstrate the effect of different parameters on the proposed algorithm's performance. Copyright © 2001 John Wiley & Sons, Ltd.
Cited by 11Open access
Fragouli, C., Seshadri, N., Turin, W. · Infoscience (Ecole Polytechnique Fédérale de Lausanne) · 2001
Cited by 0
Barbara Ripani, Andrea Modenini, G. Montorsi · GLOBECOM 2022 - 2022 IEEE Global Communications Conference · 2022
In this paper, we consider channels affected by Wiener phase noise and derive a detection algorithm that exploits oversampling at the receiver for tracking better the phase noise variations. The resulting algorithm is a multi-sample discrete-phase BCJR that outperforms receivers using a single sample per symbol and maximizes the achievable information rate over phase noise channels. Finally, we assess the suitability of the multi-sample discrete-phase BCJR for performing iterative detection and decoding with standard codes.
Cited by 0
2008
Abstract — The anomaly-based intrusion detection systems examine current system activity do find deviations from normal system activity. The present paper proposes a method for normal activity description using the Hidden Markov Models (HMM), which is tuned up using the gradient based method. The obtained model is utilized as a baseline, depicting the normal system activity. The main purpose is to distinguish the normal traces of user activity from abnormal ones using the BCJR decoding algorithm. Some results from the conducted simulation experiments are introduced as well. Index Terms — intrusion detection, anomaly-based intrusion detection, learning problem, Hidden Markov Model, BCJR decoding algorithm.
Cited by 0
Bartosz Mielczarek, Arne Svensson · 2000
: The classical method for decoding of turbocodes is the BCJR algorithm with perfect channel knowledge and synchronization. The statistics of soft bits produced by the BCJR algorithm change, however, significantly when synchronization is not ideal. Hence, soft bits can beusedinpost-processing to improve classical synchronization algorithms. This paper discusses the soft bit behaviour when the received signal is suffering from a phase or timing offset. The influenceofsynchronization parameter offset is modeled as increased pseudo-Gaussian noise power, which has been shown to provide results well agreeing with simulations. The modified signal parameters arethenused to approximate the mean behavior of the soft bit output for the first iteration. Keywords: Turbo codes, timing offset, phase offset, AWGN channel, BCJR algorithm 1. System description
Cited by 1