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About 5,167 papers for “iterative decoding”

Shuffled Iterative Decoding

J. Zhang, M.P.C. Fossorier · IEEE Transactions on Communications · 2005

Shuffled versions of iterative decoding of low-density parity-check codes and turbo codes are presented. The proposed schemes have about the same computational complexity as the standard versions, and converge faster. Simulations show that the new schedules offer better performance/complexity tradeoffs, especially when the maximum number of iterations has to remain small.

Cited by 319

Iterative equalisation-decoding scheme

Xue-Cheng Qian, Chunming Zhao, Shixin Cheng · Electronics Letters · 1999

A new iterative equalisation-decoding scheme is presented in which the decoder provides not only extrinsic information but also hard decisions of the coded bits for the next iteration. In the equaliser, the extrinsic information is used as the a priori probabilities of the transmitted bits, while hard decisions of the coded bits are utilised to improve the channel estimation. As a result, a significant gain in performance is achieved with respect to conventional iterative schemes in practical mobile channels.

Cited by 0

Iterative Decoding Using Replicas

Juntan Zhang, Yige Wang, M.P.C. Fossorier et al. · 2005

Replica shuffled versions of iterative decoders of low-density parity-check codes and turbo codes are presented in this paper. The proposed schemes can converge faster than standard and plain shuffled approaches. Two methods, density evolution and EXIT charts, are used to analyze the performance of the proposed algorithms. Both theoretical analysis and simulations show that the new schedules offer good trade-offs with respect to performance, complexity, latency and connectivity.

Cited by 1

Iterative Decoding using Eigenmessages

Todd K. Moon, John Crockett, Jacob H. Gunther et al. · IEEE Transactions on Communications · 2009

The eigenmessage approach to iterative decoding introduces a degree of nonlocality into a belief propagation decoder by representing an entire set of messages around a cycle of the Tanner graph as a linear operator. The eigenvector for the operator represents a fixed point of the belief propagation algorithm around a cycle, with incident messages fixed. A multiple eigenmessage approach is also presented, in which messages around several cycles are simultaneously expressed. The eigenmessage approach may be applied to any graph with cycles, but we demonstrate its use on LDPC decoding. In this setting, computational results compare eigenmessage methods with conventional belief propagation decoding showing, using simulation and EXIT charts, that the eigenmessage approaches slightly reduce the number of decoder iterations compared to belief propagation decoding while preserving the probability of error of conventional decoding.

Cited by 2

Iterative Source Decoding, Channel Decoding and Channel Equalisation

Jin Wang, Beng Meng, Dr. Lie-liang Yang et al. · ePrints Soton (University of Southampton) · 2007

<p>In this thesis, we apply EXtrinsic Information Transfer (EXIT) charts for analysing iterative decoding and detection schemes. We first consider a two-stage iterative source/channel decoding scheme, which is then extended to a three-stage serially concatenated turbo equalisation scheme. As a result, useful design guidelines are obtained for optimising the system’s performance.</p> <p>More explicitly, in Chapter 2 various source codes such as Huffman codes, Reversible Variable-Length Codes (RVLCs) and Variable-Length Error-Correcting (VLEC) codes are introduced and a novel algorithm is proposed for the construction of efficient RVLCs and VLEC codes. In Chapter 3, various iterative source decoding, channel decoding and channel equalisation schemes are investigated and their convergence behaviour is analysed by using EXIT charts. The effects of different source codes and channel precoders are also considered. In Chapter 4, a three-stage serially concatenated turbo equalisation scheme consisting of an inner channel equaliser, an intermediate channel code and an outer channel code separated by interleavers is proposed. With the aid of the novel concept of EXIT modules, conventional 3D EXIT chart analysis may be simplified to 2D EXIT chart analysis. Interestingly, it is observed that for the three-stage scheme relatively weak convolutional codes having short memories result in lower convergence thresholds than strong codes having long memories. Additionally, it is found that by invoking the outer and the intermediate decoder more frequently the total number of decoder activations is reduced, resulting in a relatively lower decoding complexity. Furthermore, the three-stage turbo equalisation schemes employing non-unity rate intermediate codes or IRregular Convolutional Codes (IRCCs) as the outer constituent codes are investigated. The performance of the resultant schemes is found to become gradually closer to the channel’s capacity at the expense of the increase of decoding complexity.</p>

Cited by 1

Iterative decoding in analog VLSI

Saied Hemati · 2005

lntemet, preter, distribuer et vendre des theses partout dans le monde, a des fins commerciales ou autres, sur support microforme, papier, electronique et/ou autres formats.

Cited by 6Open access

Iterative Decoding for GERAN MBMS

Wen Xu, Tiago Espinha Gasiba, Thomas Stockhammer et al. · 2006

Various advanced methods have been proposed to achieve sufficiently high throughput as well as reliability for multimedia broadcast multicast services (MBMS) within 3GPP RAN and GERAN. One of the methods which yield promising results with only marginal system modifications is based on outer Reed-Solomon (RS) coding on the radio link control (RLC) layer. For initial studies standard decoding algorithms based on erasure-only decoders have been employed. In order to further improve the performance, the system can be viewed as a serially concatenated code such that iterative decoding can be performed. Then, advanced receivers for MBMS over GERAN would incorporate soft-in soft-cut (SISO) decoders for both the inner convolutional code, as well as the outer RS code. Whereas for the convolutional code, standard SISO algorithms are applied, for the outer RS code a standard Berlekamp-Massey algorithm is modified to accept soft-input and to provide soft-output. With this modified iterative decoding strategy, simulations have shown gains of up to 14% in throughput on typical mobile radio channels.

Cited by 0

Iterative Decoding for Wireless Networks

Palanki, Ravi · CaltechTHESIS (California Institute of Technology) · 2004

The invention of turbo codes and low density parity check (LDPC) codes has made it possible for us for design error correcting codes with low decoding complexity and rates close to channel capacity. However, such codes have been studied in detail only for the most basic communication system, in which a single transmitter sends data to a single receiver over a channel whose statistics are known to both the transmitter and the receiver. Such a simplistic model is not valid in the case of a wireless network, where multiple transmitters might want to communicate with multiple receivers at the same time over a channel which can vary rapidly. While the design of efficient error correction codes for a general wireless network is an extremely hard problem, it should be possible to design such codes for several important special cases. This thesis takes a few steps in that direction. We analyze the performance of low density parity check codes under iterative decoding in certain simple networks and prove Shannon-theoretic results for more complex networks. More specifically, we analyze the iterative decoding algorithm in two very important special cases: (a) when the transmitter and receiver have no prior knowledge of the channel and (b) when the channel is a multiple access channel. We also apply iterative decoding to some non-LDPC codes on the binary symmetric channel and the additive white Gaussian noise channel. Finally, we derive capacity results for a class of wireless multicast networks and a class of fading channels.

Cited by 0Open access

Chart design of iterative decoding

Fengkui Gong, Bingbing Li, Jianhua Ge et al. · 2005

Two simple and efficient charts for iterative decoding are proposed, called output mutual information chart with defined iterative degree (DID Chart) and near optimum output mutual information chart (NOMI Chart). Compared with BER performance curve, they show the iterative performance on the whole signal-to-noise ratio range with reduced computation complexity. The concepts are illustrated for bit-interleaved coded modulation with iterative decoding (BICM-ID). Some possible usages are also presented.

Cited by 0

Iterative decoding and channel estimation

P.D. Alexander, Alex Grant · 2002

We investigate iterative decoding and channel estimation for multiple-access channels. Results are obtained concerning the fixed points of such iterations.

Cited by 23

Iterative decoding using stochastic computation

Vincent Gaudet, Anthony Rapley · Electronics Letters · 2003

An iterative decoding architecture based on stochastic computational elements is proposed. Simulation results for a simple low-density parity-check code demonstrate near-optimal performance with respect to a maximum likelihood decoder. The proposed method provides an alternative to analogue decoding for high-speed/low-power applications.

Cited by 205

Graphical Models and Iterative Decoding

S.M. Aji · 2000

Since the invention of turbo codes, there has been a lot of interest in iterative decoding schemes.It is also known that the turbo decoding algorithm and several other previously known iterative algorithms are instances of Pearl's belief propagation algorithm applied to a graph with cycles, while the algorithm is known to work only for graphs without cycles. We describe a marginalization algorithm which works on junction trees, which is based on some newer developments in Bayesian networks. This is sufficiently general that Pearl's belief propagation and decoding on Tanner graphs may be regarded as special cases. An attempt to compute the discrete Fourier transform as a marginalization problem in this framework gives the fast Fourier transform algorithm, thus showing that this framework has applications apart from probabilistic computations. Junction graphs with cycles lead to an iterative algorithm. The case of junction graphs with a single cycle is analyzed, with specific results in the case of the sum-product algorithm. We also have some experimental results for small turbo code-like junction graphs. On a different topic, we consider the typical set decoder, which can be used to obtain bounds on the noise threshold for asymptotically error free decoding, for given code ensembles. Some choices of the typical set for AWGN channel are considered and the resulting bounds on the threshold obtained.

Cited by 12