Topic
List decoding
About: List decoding is a research topic. Over the lifetime, 7251 publications have been published within this topic receiving 151182 citations.
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TL;DR: Experimental results indicate that the proposed method requires fewer iterations and improves overall system performance.
Abstract: A framework is proposed for iterative joint source-channel decoding of JPEG2000 codestreams. At the encoder, JPEG2000 is used to perform source coding with certain error-resilience (ER) modes, and LDPC codes are used to perform channel coding. During decoding, the source decoder uses the ER modes to identify corrupt sections of the codestream and provides this information to the channel decoder. Decoding is carried out jointly in an iterative fashion. Experimental results indicate that the proposed method requires fewer iterations and improves overall system performance
58 citations
TL;DR: A density evolution (DE) approach is developed for optimization of the parameters for choice of the messages to be updated and the resulting method reduces the decoding complexity by about 70-75% compared to the classical belief propagation (BP) scheme.
Abstract: A complexity reducing method for iterative message passing decoding algorithms of low-density parity-check (LDPC) codes is described. It is based on lazy scheduling which involves a partial update of messages in the iterations. A density evolution (DE) approach is developed for optimization of the parameters for choice of the messages to be updated. Combined with an efficient serial scheduling, the resulting method reduces the decoding complexity by about 70-75% compared to the classical belief propagation (BP) scheme, while maintaining the same performance
58 citations
Patent•
31 Mar 1998TL;DR: In this paper, an image decoding apparatus that generates a decoded image from a code sequence is presented, which includes an entropy decoding unit, achieved by the computer, for reading one code out of the code sequence, which is stored in the memory via the bus and performing entropy decoding on the read code in to generate a decode value.
Abstract: In an image decoding apparatus that generates a decoded image from a code sequence. The decoding apparatus has a bus, a computer and a memory, wherein the computer and the memory are connected to each other via the bus. The code sequence is generated by performing orthogonal transform, quantization and entropy coding on image data, which is stored in the memory. The decoding apparatus includes an entropy decoding unit, achieved by the computer, for reading one code out of the code sequence, which is stored in the memory, via the bus and performing entropy decoding on the read code in to generate a decode value. The apparatus also includes a coefficient generating unit, achieved by the computer, for generating at least one orthogonal transform coefficient according to the generated decode value. Also, a writing unit is achieved by the computer, for writing the generated at least one orthogonal transform coefficient into the memory via the bus. A decode controlling unit and the writing unit is provided for instructing the entropy decoding unit to process a next code out of the code sequence.
57 citations
29 Jun 1997
TL;DR: This analysis of generalized minimum distance (GMD) decoding algorithms for Euclidean space codes is presented, and it is proved that although these decoding regions are polyhedral, they are essentially always nonconvex.
Abstract: We present a detailed analysis of generalized minimum distance (GMD) decoding algorithms for Euclidean space codes. In particular, we completely characterize GMD decoding regions in terms of receiver front-end properties. This characterization is used to show that GMD decoding regions have intricate geometry. We prove that although these decoding regions are polyhedral, they are essentially always nonconvex. We furthermore show that conventional performance parameters, such as error-correction radius and effective error coefficient, do not capture the essential geometric features of a GMD decoding region, and thus do not provide a meaningful measure of performance. As an alternative, probabilistic estimates of, and upper bounds upon, the performance of GMD decoding are developed. Furthermore, extensive simulation results, for both low-dimensional and high-dimensional sphere-packings, are presented. These simulations show that multilevel codes in conjunction with multistage GMD decoding provide significant coding gains at a very low complexity. Simulated performance, in both cases, is in remarkably close agreement with our probabilistic approximations.
57 citations
TL;DR: In this article, the authors gave an explicit construction of a family of capacity-achieving binary t-write WOM codes for any number of writes t, which have polynomial time encoding and decoding algorithms.
Abstract: In this paper, we give an explicit construction of a family of capacity-achieving binary t-write WOM codes for any number of writes t, which have polynomial time encoding and decoding algorithms. The block length of our construction is N=(t/e)O(t/(δe)) when e is the gap to capacity and encoding and decoding run in time N1+δ. This is the first deterministic construction achieving these parameters. Our techniques also apply to larger alphabets.
57 citations