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US 6,389,574 B1Granted
Method for detecting a discrete symbol sequence from an observation signal, and viterbi processor implementing such method
AssigneeMatra Nortel Communications
InventorsFabrice Belveze, Florence Chancel
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Abstract
The detection of symbols of a sequence on the basis of an observation signal is performed in accordance with a soft output Viterbi algorithm using a trellis. In order to assign a likelihood to a discrete estimation of a symbol, the difference between the metrics of the optimal path determined in accordance with the Viterbi algorithm and the metrics of a competitor path, which is optimal among all the paths leading to a different decision for the symbol in question is calculated, the metrics being considered on the whole length of the trellis.
Claims26
A method for detecting a discrete symbol sequence from an observation signal the production of which can be described by means of a trellis of NE states Ee (0≦e<NE) and NB branches Bb (0≦b<NB), each branch having a start state and an arrival state among the NE states and being associated with a single Q-uplet of discrete symbols, Q being an integer at least equal to 1,
- the trellis comprising paths each formed by a succession of branches, each path having a metric defined by a sum of elementary metrics relative to the successive branches forming said path, and being associated with a single possible sequence of discrete symbols formed by the succession of Q-uplets with which the successive branches forming said path are respectively associated,
- wherein the observation signal is processed by successive time segments, the processing of a segment n of the observation signal including:
- for each of the NB branches Bb (0≦b<NB), obtaining an elementary metric corresponding to a combination between the segment n of the observation signal and a reference signal associated with the branch Bb, and the calculation of an accumulated branch metric MBAb(n) by adding the elementary metric obtained to an accumulated state metric MEAe(n−1) relative to the start state Ee of the branch Bb;
- and
- for each of the NE states Ee (0≦e<NE), updating the accumulated state metric MEAe(n), taken as equal to an optimum of the accumulated branch metrics MBAb(n) relative to those of the branches Bb which have the state Ee as the arrival state, and storing an identification of a surviving branch for which said optimum is reached,
- wherein, after processing successive segments of the observation signal, a selection is made of one of the NE states Ee0 and of an optimal path αopt of the trellis formed by returning up the surviving branches from the selected state, and at least one discrete symbol Dm of the sequence to be detected is estimated by the value of a corresponding symbol of the sequence with which the selected optimal path is associated,
- wherein, for each symbol Dm of the sequence to be detected, estimated after the selection of a state Ee0 and of an optimal path αopt, a minimum difference in metrics is calculated between the optimal path and a competitor path associated with a sequence in which the symbol corresponding to the symbol Dm has a value other than the estimation retained for the symbol Dm,
- and wherein a likelihood Λm of the estimation of each symbol Dm is determined as a function of the minimum difference in metrics calculated for said symbol Dm.
5 more elements
A Viterbi processor, for detecting a discrete symbol sequence from an observation signal the production of which can be described by means of a trellis of NE states Ee (0≦e<NE) and NB branches Bb (0≦b<NB), each branch having a start state and an arrival state among the NE states and being associated with a single Q-uplet of discrete symbols, Q being an integer at least equal to 1,
- the trellis comprising paths each formed by a succession of branches, each path having a metric defined by a sum of elementary metrics relative to the successive branches forming said path, and being associated with a single possible sequence of discrete symbols formed by the succession of Q-uplets with which the successive branches forming said path are respectively associated,
- including elementary metrics calculation means for calculating elementary metrics MBb(n) each corresponding to a combination between a time segment n of the observation signal and a reference signal associated with one of the NB branches Bb, and sequential processing means for processing the observation signal by successive time segments, arranged to carry out, for each segment n of the observation signal, a processing including:
- for each of the NB branches Bb (0≦b<NB), the calculation of an accumulated branch metric MBAb(n) by adding the elementary metric MBb(n), provided by the elementary metrics calculation means to an accumulated state metric MEAe(n−1) relative to the start state Ee of the branch Bb;
- and
- for each of the NE states Ee (0≦e<NE), the updating of the accumulated state metric MEAe(n), taken as equal to an optimum of the accumulated branch metrics MBAb(n) relative to those of the branches Bb which have the state Ee as the arrival state, and the storage of an identification of a surviving branch for which said optimum is reached,
- wherein the sequential processing means are arranged to select one of the NE states Ee0 and an optimal path αopt of the trellis after processing successive segments of the observation signal, the optimal path αopt being formed by returning up the surviving branches from the selected state, in order to estimate at least one discrete symbol Dm of the sequence to be detected by the value of a corresponding symbol of the sequence with which the selected optimal path is associated,
- and wherein the sequential processing means are further arranged to calculate, for each symbol Dm of the sequence to be detected, estimated after the selection of a state Ee0 and an optimal path αopt, a minimum difference in metrics between the optimal path and a competitor path associated with a sequence of which the symbol corresponding to the symbol Dm has a value other than the estimation sequence for the symbol Dm, and to determine a likelihood Λm of the estimation of the symbol Dm as a function of the calculated minimum difference in metrics.
4 more elements
A digital signal demodulator, including channel estimation means to determine, from an observation signal, reference signals respectively associated with NB branches of a trellis, and a Viterbi processor receiving the reference signals and the observation signal distributed in successive segments, and producing estimations of discrete symbols processed by a modulator and likelihoods respectively associated with said estimations,
- wherein the trellis, describing the production of the observation signal, has NE states Ee (0≦e<NE) and NB branches Bb (0≦b<NB), each branch having a start state and an arrival state among the NE states and being associated with a single Q-uplet of discrete symbols, Q being an integer at least equal to 1,
- the trellis comprising paths each formed by a succession of branches, each path having a metric defined by a sum of elementary metrics relative to the successive branches forming said path, and being associated with a single possible sequence of discrete symbols formed by the succession of Q-uplets with which the successive branches forming said path are respectively associated,
- wherein the Viterbi processor comprises elementary metrics calculation means for calculating elementary metrics MBb(n) each corresponding to a combination between a time segment n of the observation signal and the reference signal associated with one of the NB branches Bb, and sequential processing means for processing the observation signal by successive time segments, arranged to carry out, for each segment n of the observation signal, a processing including:
- for each of the NB branches Bb (0≦b<NB), the calculation of an accumulated branch metric MBAb(n) by adding the elementary metric MBb(n), provided by the elementary metrics calculation means to an accumulated state metric MEAe(n−1) relative to the start state Ee of the branch Bb;
- and
- for each of the NE states Ee (0≦e<NE), the updating of the accumulated state metric MEAe(n), taken as equal to an optimum of the accumulated branch metrics MBAb(n) relative to those of the branches Bb which have the state Ee as the arrival state, and the storage of an identification of a surviving branch for which said optimum is reached,
- wherein the sequential processing means of the Viterbi processor are arranged to select one of the NE states Ee0 and an optimal path αopt of the trellis after processing successive segments of the observation signal. the optimal path αopt being formed by returning up the surviving branches from the selected state, in order to estimate at least one discrete symbol Dm by the value of a corresponding symbol of the sequence with which the selected optimal path is associated,
- and wherein the sequential processing means of the Viterbi processor are further arranged to calculate, for each symbol Dm estimated after the selection of a state Ee0 and an optimal path αopt, a minimum difference in metrics between the optimal path and a competitor path associated with a sequence of which the symbol corresponding to the symbol Dm has a value other than the estimation retained for the symbol Dm, and to determine the likelihood Λm of the estimation of the symbol Dm as a function of the calculated minimum difference in metrics.
5 more elements
A digital signal decoder, including a Viterbi processor receiving an observation signal distributed in successive segments, and producing estimations of discrete symbols processed by an encoder and likelihoods respectively associated with said estimations,
- wherein the production of the observation signal can be described by means of a trellis of NE states Ee (0≦e<NE) and NB branches Bb (0≦b<NB), each branch having a start state and an arrival state among the NE states and being associated with a single Q-uplet of discrete symbols, Q being an integer at least equal to 1,
- the trellis comprising paths each formed by a succession of branches, each path having a metric defined by a sum of elementary metrics relative to the successive branches forming said path, and being associated with a single possible sequence of discrete symbols formed by the succession of Q-uplets with which the successive branches forming said path are respectively associated,
- wherein the Viterbi processor comprises elementary metrics calculation means for calculating elementary metrics MBb(n) each corresponding to a combination between a time segment n of the observation signal and a reference signal associated with one of the NB branches Bb, and sequential processing means for processing the observation signal by successive time segments, arranged to carry out, for each segment n of the observation signal, a processing including:
- for each of the NB branches Bb (0≦b<NB), the calculation of an accumulated branch metric MBAb(n) by adding the elementary metric MBb(n), provided by the elementary metrics calculation means to an accumulated state metric MEAe(n−1) relative to the start state Ee of the branch Bb;
- and
- for each of the NE states Ee (0≦e<NE), the updating of the accumulated state metric MEAe(n), taken as equal to an optimum of the accumulated branch metrics MBAb(n) relative to those of the branches Bb which have the state Ee as the arrival state, and the storage of an identification of a surviving branch for which said optimum is reached,
- wherein the sequential processing means of the Viterbi processor are arranged to select one of the NE states Ee0 and an optimal path αopt of the trellis after processing successive segments of the observation signal, the optimal path αopt being formed by returning up the surviving branches from the selected state, in order to estimate at least one discrete symbol Dm by the value of a corresponding symbol of the sequence with which the selected optimal path is associated,
- and wherein the sequential processing means of the Viterbi processor are further arranged to calculate, for each symbol Dm estimated after the selection of a state Ee0 and an optimal path αopt, a minimum difference in metrics between the optimal path and a competitor path associated with a sequence of which the symbol corresponding to the symbol Dm has a value other than the estimation retained for the symbol Dm, and to determine the likelihood Λm of the estimation of the symbol Dm as a function of the calculated minimum difference in metrics.
5 more elements
Dependencies are inferred from the claim text.