US 5,406,570 AGranted

Method for a maximum likelihood decoding of a convolutional code with decision weighting, and corresponding decoder

AssigneeFrance Telecom and Telediffusion de France

InventorsClaude Berrou, Patrick Adde

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Abstract

A method for the decoding of digital data obtained according to a convolutional coding and transmitted on a noise-ridden channel aimed at improving the methods of maximum likelihood decoding such as the Viterbi algorithm consisting in associating, with each estimation s(t) of the corresponding source digital element a(t), a weighting coefficient m(t) representing the reliability of the estimation s(t), the estimation s(t) taking account of the values of a first series of L received samples, and the weighting m(t) taking account of the values of a second series of N samples received, N being strictly greater than L. In a preferred embodiment, a second trellis is associated with the standard first decoding trellis, a trace-back being done in the second trellis on two concurrent paths, used to revise the weighting coefficients obtained at output of the first trellis.

Claims13

Dependent claims

A method for maximum likelihood decoding of a digital signal transmitted in the presence of noise using reduced storage and processing means providing for improved weighting, the method comprising the steps of

receiving at a receiver a sequence of received samples R(t) corresponding to a convolutional coding of a source digital elements a(t) of a signal transmitted in the presence of noise,
estimating an estimation value s(t) of each of said source digital elements a(t) taking account of a first series of L received samples, including said received sample R(t) corresponding to said source digital element a(t) and the following L-1 received samples R(t+1), . . . ,R(t+L-1), L being an integer strictly greater than 1,
computing a weighting coefficient m(t) representing reliability of said estimation value s(t), taking account of a second series of N received samples, comprising said received sample R(t) corresponding to said source digital element a(t) and the following N-1 received samples R(t+1), . . . , R(t+L-1), . . . , R(t+N-1), N being an integer strictly greater than L, and
associating with each of said received Sample R(t) said estimation value s(t) along with said weighting coefficient m(t) to identify at the receiver the most likely coding of the source digital elements a (t).

1 more element

A decoder of a sequence of received samples R(t), corresponding to a convolutional coding of a sequence of source digital elements a(t), said decoder comprising:

first and second storing means operating as level-by-level shift registers;
said first storing means being designed for storing a first trellis T(2.sup..nu.,L) of the possible states of the coding, comprising a set of nodes, organized in L depth levels of 2.sup..nu. nodes, L being an integer strictly greater than 1, and
said second storing means being designed for storing a second trellis T'(2.sup..nu.,L') of the possible states of the coding, comprising a set of nodes, organized in L' depth levels, of 2.sup..nu. nodes, L' being an integer strictly greater than 1,
said second storing means being connected consecutively to said first means for storing, so that said first storing means stores data corresponding to instants of reception between t and t-L and said second storing means stores data corresponding to instants of reception between t-L-1 and t-L-L';
means for tracing back of an optimal path ending with a final node, in said first trellis stored in said first means storing;
means for tracing back of two concurrent paths in said second trellis stored in said second means storing;
means for computing concurrence indices for each node of said first trellis;
third storing means of all concurrence indices associated with each node of said first trellis, with a size L.times.2.sup..nu. .times..mu., where .mu. is the number of bits used for the coding of each concurrence index;
a shift register, for storing weighting coefficients m(t-L-1) to m(t-N);
and
means for revision of said weighting coefficients, as a function of said two concurrent paths traced back to said second trellis.

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Dependencies are inferred from the claim text.