Skip to content
Free planNo credit card requiredStart writing
AI for Research home
AI for Research home
Dashboard
Sign inGet started

Search 250 million research papers

Read the abstract, see who wrote it and who cites it, and get the citation in APA, MLA, Chicago or Harvard.

About 135 papers for “Iterative Viterbi decoding”

Iterative Viterbi decoding, trellis shaping, and multilevel structure for high-rate parity-concatenated TCM

Qi Wang, Lei Wei, Rodney A. Kennedy · IEEE Transactions on Communications · 2002

We define and apply a new algorithm called the iterative Viterbi decoding algorithm (IVA) to decode a high-rate parity-concatenated TCM system in which a trellis code is used as the inner code and a simple parity-check code is used as the outer code. With trellis shaping, the IVA can achieve a performance 1.25 dB away from the Shannon limit at a BER of 3/spl times/10/sup -5/ with low complexity. By augmenting the system with a binary BCH code, the error floor can be reduced to 10/sup -9/ with very little additional cost.

Cited by 21

Codes and iterative decoding on general graphs

N. Wiberg, Hans‐Andrea Loeliger, Ralf Kötter · European Transactions on Telecommunications · 1995

Abstract A general framework, based on ideas of Tanner, for the description of codes and iterative decoding (“turbo coding”) is developed. Just like trellis‐based code descriptions are naturally matched to Viterbi decoding, code descriptions based on Tanner graphs (which may be viewed as generalized trellises) are naturally matched to iterative decoding. Two basic iterative decoding algorithms (which are versions of the algorithms of Berrou et al. and of Hagenauer, respectively) are shown to be natural generalizations of the forward‐backward algorithm (Bahl et al.) and the Viterbi algorithm, respectively, to arbitrary Tanner graphs. The careful derivation of these algorithms clarifies, in particular, which a priori probabilities are admissible and how they are properly dealt with. For cycle codes (a class of binary linear block codes), a complete characterization is given of the error patterns that are corrected by the generalized Viterbi algorithm after infinitely many iterations.

Cited by 314

Improved upper bound on the bit error probability of turbo codes for ML decoding with imperfect CSI in a Rayleigh fading channel

Hyundong Shin, Jae Hong Lee · 2002

We investigate an improved upper bound on the bit error probability of turbo codes for the maximum likelihood (ML) decoding with imperfect channel state information (CSI) in a fully interleaved Rayleigh fading channel. The upper bound is based on the Viterbi & Viterbi (see Proc. of the IEEE Inform. Theory Workshop '98, San Diego, CA, Feb. 1998, p.72) bound and is also compared with iterative decoding using the log-MAP algorithm. It is shown that the upper bound well approximates the simulation results of the iterative decoding below a BER of 10/sup -5/.

Cited by 3

Iterative Decoding between Two-Dimensional Soft Output Viterbi Algorithm and Error Correcting Modulation Code for Holographic Data Storage

Jin‐Young Kim, Yong Moon, Jaejin Lee · Japanese Journal of Applied Physics · 2011

We propose an iterative decoding scheme for holographic data storage that uses modulation codes with a trellis structure to obtain some coding gain. Furthermore, the iterative scheme between a channel detector and the modulation code can achieve more coding gain. In the simulation, when there are (10%, 10%) and (20%, 20%) misalignments, the proposed iterative scheme with a pseudorandom interleaver performs approximately 0.3 and 1 dB better, respectively, compared to the scheme without iteration.

Cited by 14

Iterative channel decoding for PC-based software radio DVB-T receiver

Jiancheng Yu, Yueh-Teng Hsu, Shin-En Wang et al. · 2011

We propose a hard iterative channel decoding for a PC-based DVB-T software receiver testbed. By Reed-Solomon (RS) decoder, we make the error symbols have maximum Euclidean distance and thus no chosen in Viterbi decoding.

Cited by 2

Coding with a latency constraint: The benefits of sequential decoding

Shashank V. Maiya, Daniel J. Costello, Thomas E. Fuja et al. · 2010

This paper compares the performance of convolutional codes to that of LDPC block codes with identical decoding latencies. The decoding algorithms considered are the Viterbi algorithm and stack sequential decoding for convolutional codes and iterative message passing for LDPC codes. It is shown that, at very low latencies, convolutional codes with Viterbi decoding offer the best performance, whereas for high latencies LDPC codes dominate - and sequential decoding of convolutional codes offers the best performance over a range of intermediate latency values. The “crossover latencies” - i.e., the latency values at which the best code/decoding selection changes - are identified for a variety of code rates (1/2, 2/3, 3/4, and 5/6) and target bit/frame error rates. Thus, sequential decoding can substantially extend the range of latency values over which continuous decoding of convolutional codes proves advantageous compared to LDPC block codes, beyond what is observed when only Viterbi decoding is employed.

Cited by 20

Iterative Decision Feedback Equalizer for Coded ISI Channels

Lu Jing · 2001

In this paper,we show that the performance of conventional Decision Feedback Equ alizer (DFE) followed by Viterbi decoding for coded Inter Symbol Interference ( ISI) channels may be improved significantly by iterative use of decoding information.At each iteration,DFE may outperform its original form since now feedback decisions are more reliable as some errors are corrected by Viterbi decoding.The proposed algorithms may find some practical applications since they have relatively low complexity.

Cited by 0

Design and performance of a low-complexity iterative multiuser joint decoder based on Viterbi decoding and parallel interference cancellation

Alessandro Nordio, M.A. Lagunas, G. Caire · 2003

We propose a low-complexity multiuser joint parallel interference cancellation (PIC) decoder for direct-sequence CDMA. An estimate of the multiple-access interference (MAI) signal is formed by weighting the hard decisions produced by hard-output Viterbi decoders. Such MAI interference estimate is subtracted from the received signal in order to improve decoding in the next iteration. By using asymptotic performance analysis of random-spreading CDMA, we optimize the feedback weights at each iteration. Then, we consider two performance limitation factors: the bias of residual interference and the ping-pong effect. We propose then a modification of the basic PIC algorithm, which allows higher channel load and/or faster convergence to the single-user performance. The main conclusion of this work is that, in most practical cases, SISO decoders are not needed to attain very high spectral efficiency, and simple conventional Viterbi decoding suffices for most practical settings.

Cited by 4

On bootstrap iterative Viterbi algorithm

Lei Wei · 2003

A bootstrap iterative Viterbi algorithm (BIVA) is proposed based on a bootstrap structure. Two different modifications are then considered for both very short size blocks (say 100-250 bits) and the medium size blocks (1000-3000 bits). It shows that the iterative decoding can be achieved by using the conventional Viterbi algorithm, which does not require the noise variance estimation. The numerical results show the significant performance improvement over the standard Viterbi algorithm is possible. For a block length of 1500 bits and with a 32 state VA, the 2D BIVA can achieve a bit error rate of 2/spl times/10/sup -5/ at an E/sub b//E/sub 0/ of 2.3 dB away from the Shannon limit. For both information block lengths of 1944 and 11970 bits, in term of its performance respect to the Shannon limit and the Shannon sphere packing bound, the 2D-BIVA is about 0.2-0.3 dB worse than the best known rate 1/2 JPL turbo codes of similar information block sizes. With some simple modifications, most of current systems (where the Viterbi algorithms used) can benefit significantly from this iterative decoding procedure.

Cited by 7

Turbo convolution codes

Šedý, Jakub, Šilhavý, Pavel · Brno University of Technology Digital Library (Brno University of Technology) · 2011

The article deals with turbo convolutional codes. There is disassembled encoding these codes and iterative decoding principle of using the Viterbi algorithm with soft output. It is evaluated the performance of turbo codes based on the simulations.

Cited by 0

Codes and iterative decoding on general graphs

N. Wiberg, Hans‐Andrea Loeliger, Ralf Kötter · 2002

Until recently, most known decoding procedures for error-correcting codes were based either on algebraically calculating the error pattern or on some sort of tree or trellis search. With the advent of turbo coding, a third decoding principle has finally had its breakthrough: iterative decoding. With respect to Viterbi decoding, a code is most naturally described by means of a trellis diagram. The main thesis of the present paper is that, with respect to iterative decoding, the natural way of describing a code is by means of a Tanner graph, which may be viewed as a generalized trellis. More precisely, it is the "time axis" of a trellis that is generalized to a Tanner graph.

Cited by 95

Iterative interference cancellation and decoding for convolutional coded VBLAST systems

Yan Wu, Sumei Sun · 2004

In this paper, we present an iterative interference cancellation (IIC) and decoding scheme that significantly improves the performance of coded VBLAST systems. We show that due to the residue interference caused by incorrect decisions from the previous iteration, the distribution of the total noise in the IIC process is non-Gaussian. Euclidean distance therefore cannot be used as the bit metric in soft decision Viterbi decoding. To preserve the Gaussian distribution of the total noise, we propose to use soft nulling for VBLAST detection. We also propose a scheme employing soft decision Viterbi decoding with IIC (SDD-IIC) and demonstrate that it significantly improves both the coding gain and diversity gain of the VBLAST system.

Cited by 3

Performance Comparison of Latency for RSC-RSC and RS-RSC Concatenated Codes

Manish Kumar, Jyoti Saxena · Indonesian Journal of Electrical Engineering and Informatics (IJEEI) · 2013

In this paper, we compare the latency of serially concatenated convolutional codes. In particular, we compare RSC-RSC concatenated codes using non-iterative concatenated Viterbi decoding to RS-RSC concatenated codes using concatenation of Viterbi & Berklelamp-Massey decoding. We have also used puncturing to obtain different code rates & analyzed the effect of code rate on latency. On the basis of simulations, it is shown that RSC-RSC code is better than RS-RSC codes for low latency applications. It is also shown that a trade-off is needed between BER & latency for concatenated codes.

Cited by 4Open access

On the use of SOVA for iterative decoding

Yasmine Fahmy, H.A.G. Abdel Kader, M. El-Soudani · 2003

Most of the error correcting capabilities rely on the concept of iterative decoding. However, the iterative decoding needs a "soft-in/soft-out" component decoders. Such decoders can be realized either by using maximum a posteriori (MAP) symbol by symbol estimator or the soft output Viterbi algorithm (SOVA). The latter is more suitable for hardware implementation. Therefore, improving the performance of the SOVA is very important to future applications where novel class of codes such as turbo codes are used. In this paper, motivated by improving the hardware implementation, we study the relation between the updating depth, a parameter of the SOVA, and the number of iterations defined by the iterative decoding procedure.

Cited by 2

Iterative decoding of product codes

O. Al-Askary · KTH Publication Database DiVA (KTH Royal Institute of Technology) · 2003

Iterative decoding of block codes is a rather old subjectthat regained much interest recently. The main idea behinditerative decoding is to break up the decoding problem into asequence of stages, iterations, such that each stage utilizesthe output from the previous stages to formulate its ownresult. In order for the iterative decoding algorithms to bepractically feasible, the complexity in each stage, in terms ofnumber of operations and hardware complexity, should be muchless than that for the original non-iterative decoding problem.At the same time, the performance should approach the optimum,maximum likelihood decoding performance in terms of bit errorrate. In this thesis, we study the problem of iterative decodingof product codes. We propose an iterative decoding algorithmthat best suits product codes but can be applied to other blockcodes of similar construction. The algorithm approaches maximumlikelihood performance. We also present another algorithm whichis suboptimal and can be viewed as a practical implementationof the rst algorithm on product codes. The performance of thesuboptimal algorithm is investigated both analytically and bycomputer simulations. The complexity is also investigated andcompared to the complexity of GMD and Viterbi decoding ofproduct codes.

Cited by 7Open access

Receding horizon decoding of convolutional codes

José Ignacio Iglesias Curto, Uwe Helmke · ArXiv.org · 2009

Decoding of convolutional codes poses a significant challenge for coding theory. Classical methods, based on e.g. Viterbi decoding, suffer from being computationally expensive and are restricted therefore to codes of small complexity. Based on analogies with model predictive optimal control, we propose a new iterative method for convolutional decoding that is cheaper to implement than established algorithms, while still offering significant error correction capabilities. The algorithm is particularly well-suited for decoding special types of convolutional codes, such as e.g. cyclic convolutional codes.

Cited by 1Open access

Модифікація алгоритму Bi-SOVA для декодування Турбокодів множення

Топалов, Владислав Владимирович · The Scientific Issues of Ternopil Volodymyr Hnatiuk National Pedagogical University Series pedagogy · 2014

A modification of the bi-directional iterative soft-output Viterbi algorithm (Bi - SOVA) for decoding of turbo product codes is proposed. It was shown that the modification reduces the number of mathematical operations of comparison. An assessment of modification effectiveness is done. It is conducted the simulation of data channel of turbo codes with different parameters work which showed that the loss of energy efficiency of the decoding algorithm is compared with the modification to the algorithm without modification is not detected. These results allow to recommend the use of modified algorithm in the receiving equipment to reduce the computational complexity of the device and, therefore, reduce the cost of the final product. Further study may be devoted to the modeling of other channels of communication with other parameters of turbo product codes and assessing the modification effectiveness of bi-directional iterative soft-output Viterbi algorithm (Bi - SOVA) for decoding the codes of product.

Cited by 0Open access