Sequential decoding

About: Sequential decoding is a research topic. Over the lifetime, 8667 publications have been published within this topic receiving 204271 citations.

Fundamentals of bar code information theory

Abstract: To compare encoding and decoding schemes requires one to first look into information and coding theory. This article discusses problems and possible solutions in encoding information. >

Capacity-approaching turbo coding and iterative decoding for relay channels

Abstract: In this paper, we design turbo-based coding schemes for relay systems together with iterative decoding algorithms. In the proposed schemes, the source node sends coded information bits to both the relay and the destination nodes, while the relay simultaneously forwards its estimate for the previous coded block to the destination after decoding and re-encoding. The destination observes a superposition of the codewords and uses an iterative decoding algorithm to estimate the transmitted messages. Different from the block-by-block decoding techniques used in the literature, this decoding scheme operates over all the transmitted blocks jointly. Various encoding and decoding approaches are proposed for both single-input single-output and multi-input multi-output systems over several different channel models. Capacity bounds and information-rate bounds with binary inputs are also provided, and it is shown that the performance of the proposed practical scheme is typically about 1.0-1.5 dB away from the theoretical limits, and a remarkable advantage can be achieved over the direct and multihop transmission alternatives.

Serial concatenation of block and convolutional codes

Abstract: Parallel concatenated coding schemes employing convolutional codes as constituent codes linked by an interleaver have been proposed in the literature as ‘turbo codes’. They yield very good performance in connection with simple suboptimum decoding algorithms. The authors propose an alternative scheme consisting in the serial concatenation of block or convolutional codes and evaluate its average performance in terms of bit error probability.

Determinate state convolutional codes

Abstract: A determinate state convolutional code is formed from a conventional convolutional code by pruning away some of the possible state transitions in the decoding trellis. This staged power transfer proves to be an extremely efficient way of enhancing the performance of a concatenated coding system. The authors analyze the decoding complexity and free distances of these new codes, determine some important statistical properties of the decoder output, and provide simulation results for performance at the low signal-to-noise ratios where a real communications system would operate. Several concise, practical examples are presented. >

Efficient priority-first search maximum-likelihood soft-decision decoding of linear block codes

Abstract: The authors present a novel and efficient maximum-likelihood soft-decision decoding algorithm for linear block codes. The approach used here converts the decoding problem into a search problem through a graph that is a trellis for an equivalent code of the transmitted code. A generalized Dijkstra's algorithm, which uses a priority-first search strategy, is employed to search through this graph. This search is guided by an evaluation function f defined to take advantage of the information provided by the received vector and the inherent properties of the transmitted code. This function f is used to reduce drastically the search space and to make the decoding efforts of this decoding algorithm adaptable to the noise level. For example, for most real channels of the 35 000 samples tried, simulation results for the (128,64) binary extended BCH code show that the proposed decoding algorithm is fifteen orders of magnitude more efficient in time and in space than that proposed by Wolf (1978). Simulation results for the (104, 52) binary extended quadratic residue code are also given. >