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List decoding

About: List decoding is a research topic. Over the lifetime, 7251 publications have been published within this topic receiving 151182 citations.


Papers
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Journal ArticleDOI
TL;DR: This paper presents an improved architecture for successive-cancellation decoding of polar codes, making use of a novel semi-parallel, encoder-based partial-sum computation module, and explores various optimization techniques such as a chained processing element and a variable quantization scheme.
Abstract: Polar codes are the first error-correcting codes to provably achieve channel capacity, asymptotically in code length, with an explicit construction. However, under successive-cancellation decoding, polar codes require very long code lengths to compete with existing modern codes. Nonetheless, the successive cancellation algorithm enables very-low-complexity implementations in hardware, due to the regular structure exhibited by polar codes. In this paper, we present an improved architecture for successive-cancellation decoding of polar codes, making use of a novel semi-parallel, encoder-based partial-sum computation module. We also provide quantization results for realistic code length N=2 15 , and explore various optimization techniques such as a chained processing element and a variable quantization scheme. This design is shown to scale to code lengths of up to N=2 21 , enabled by its low logic use, low register use and simple datapaths, limited almost exclusively by the amount of available SRAM. It also supports an overlapped loading of frames, allowing full-throughput decoding with a single set of input buffers.

52 citations

Journal ArticleDOI
TL;DR: A new continuous version of the maximum a posteriori algorithm is described and applied to sequence oriented decoding of parallel concatenated convolutional codes.
Abstract: A new continuous version of the maximum a posteriori algorithm is described and applied to sequence oriented decoding of parallel concatenated convolutional codes

52 citations

Journal ArticleDOI
TL;DR: This paper discusses the use of two types of convolutional codes, diffuse threshold-decoded codes and Gallager codes, on channels with memory (burst channels), and proves that, for one important diffuse code, propagation is finite and small.
Abstract: This paper discusses the use of two types of convolutional codes, diffuse threshold-decoded codes and Gallager codes, on channels with memory (burst channels) The operation of these codes is explained and test results are given for a variety of equipments operated over phone line, HF radio, and troposcatter channels Error propagation in the threshold-decoded codes is discussed and, in the Appendix, we prove that, for one important diffuse code, propagation is finite and small

52 citations

Patent
13 Apr 2005
TL;DR: In this paper, a decoding scheme for LDPC (Low-Density Parity-Check) codes using sequential decoding has been proposed, where the nodes are divided according to a parity-check matrix into check nodes for a parity check message and variable nodes for bit messages.
Abstract: Disclosed is a decoding apparatus for LDPC (Low-Density Parity-Check) codes when receiving data encoded with LDPC codes on a channel having consecutive output values, and a method thereof The decoding method for LDPC codes uses sequential decoding and includes the following steps: (a) the nodes are divided according to a parity-check matrix into check nodes for a parity-check message and variable nodes for a bit message; (b) the check nodes are divided into a predetermined number of subsets; (c) the LDPC codeword of each subset for all the check nodes is sequentially decoded; (d) an output message is generated for verifying validity of the decoding result; and (e) the steps (b), (c), and (d) are iteratively performed by a predetermined number of iterations

52 citations

Journal ArticleDOI
TL;DR: The recently introduced threaded cyclic-division-algebra-based codes are shown to take a particularly concise form as a non-monotonic function of the multiplexing gain, which describes the minimum known complexity of any decoder that can provably achieve a gap to maximum likelihood performance that vanishes in the high SNR limit.
Abstract: In the setting of quasi-static multiple-input multiple-output channels, we consider the high signal-to-noise ratio (SNR) asymptotic complexity required by the sphere decoding (SD) algorithm for decoding a large class of full-rate linear space-time codes. With SD complexity having random fluctuations induced by the random channel, noise, and codeword realizations, the introduced SD complexity exponent manages to concisely describe the computational reserves required by the SD algorithm to achieve arbitrarily close to optimal decoding performance. Bounds and exact expressions for the SD complexity exponent are obtained for the decoding of large families of codes with arbitrary performance characteristics. For the particular example of decoding the recently introduced threaded cyclic-division-algebra-based codes—the only currently known explicit designs that are uniformly optimal with respect to the diversity multiplexing tradeoff—the SD complexity exponent is shown to take a particularly concise form as a non-monotonic function of the multiplexing gain. To date, the SD complexity exponent also describes the minimum known complexity of any decoder that can provably achieve a gap to maximum likelihood performance that vanishes in the high SNR limit.

52 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202384
2022153
202179
202078
201982
201894