SPATIAL-MULTIPLEXED SIGNAL DETECTION METHOD AND SPATIAL AND TEMPORAL ITERATIVE DECODER THAT USES THIS METHOD
First Claim
1. A spatial-multiplexed signal detection method wherein, in a soft-input soft-output detection method in spatial and temporal multiplexed signal separation, a process (factorization) is included for implementing factorization of conditional probability referred to as “
- likelihood”
that is obtained for a signal sequence that is received when a spatial-multiplexed transmission sequence is assumed to have been transmitted such that the conditional probability can be represented as the product of a plurality of conditional probabilities;
the conditional probabilities for which factorization is possible are divided into a plurality of groups;
when calculating the likelihoods, an ordering can be established among said groups for which probabilities are calculated such that the groups that include events that are the conditions of the conditional probabilities in said groups are processed earlier; and
when calculating probabilities in the groups, a metric operation method is used that uses semi-rings for estimating transmission sequences by means of the ratio of the likelihoods of two exclusive events.
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Abstract
The present invention is directed to providing a spatial-multiplexed signal detection method that can improve the characteristics of spatial and temporal iterative decoding that is based on turbo principles. According to the method, when implementing factorization of conditional probability referred to as “likelihood” such that the conditional probability can be represented by the product of a plurality of conditional probabilities, the conditional probability being obtained for a received signal sequence in a spatial and temporal iterative decoding configuration based on turbo principles of soft-input soft-output detector 1 and soft-input soft-output decoder 2, the conditional probability for which factorization is possible is divided into a plurality of groups. When calculating this likelihood, the ordering among groups in which probabilities are calculated can be ordered such that groups that contain events that serve as the conditions of conditional probabilities in the groups are processed earlier. When calculating the probabilities in the groups, a metric operation method is used that uses semi-rings for estimating transmission sequences by means of the ratio of likelihoods of two exclusive events.
19 Citations
18 Claims
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1. A spatial-multiplexed signal detection method wherein, in a soft-input soft-output detection method in spatial and temporal multiplexed signal separation, a process (factorization) is included for implementing factorization of conditional probability referred to as “
- likelihood”
that is obtained for a signal sequence that is received when a spatial-multiplexed transmission sequence is assumed to have been transmitted such that the conditional probability can be represented as the product of a plurality of conditional probabilities;
the conditional probabilities for which factorization is possible are divided into a plurality of groups;
when calculating the likelihoods, an ordering can be established among said groups for which probabilities are calculated such that the groups that include events that are the conditions of the conditional probabilities in said groups are processed earlier; and
when calculating probabilities in the groups, a metric operation method is used that uses semi-rings for estimating transmission sequences by means of the ratio of the likelihoods of two exclusive events. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 16, 17, 18)
- likelihood”
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9. A spatial-multiplexed signal detection method wherein, in a soft-input soft-output detection method in spatial and temporal multiplexed signal separation, a process (factorization) is included for implementing factorization of conditional probability referred to as “
- likelihood”
that is obtained for a signal sequence that is received when a spatial-multiplexed transmission sequence is assumed to have been transmitted such that the conditional probability can be represented as the product of a plurality of conditional probabilities;
the conditional probabilities for which factorization is possible are divided into a plurality of groups;
when calculating the likelihoods, an order can be established among said groups for which probabilities are calculated such that said groups that include events that are the conditions of conditional probabilities in said groups are processed earlier;
when calculating conditional probabilities in each group, a process is included for calculating, as the condition of the conditional probability, a transmission sequence that indicates the maximum conditional probability in said group that contains an event that is the condition of the conditional probability in its own group, and for calculating, based on the transmission sequence that indicates the maximum conditional probability of the preceding stage, the conditional probability in each group in accordance with said ordering among the groups; and
a metric operation method is used that uses semi-rings for estimating a transmission sequence that maximizes said likelihood;
and further, as resampling after completion of processing in the final stage, processes are included for selecting the metric-base maximum likelihood from a set of combinations of said conditional probabilities in which bits that are targets have been calculated as targets of estimation, and moreover, selecting the metric-base maximum likelihood from the set of combinations of said conditional probabilities in which exclusive events for the target bits have been calculated as the targets of estimation; and
a process is included for taking the difference between the two metrics as the soft determination output of the target bits.
- likelihood”
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10. A spatial and temporal iterative decoder in spatial and temporal multiplexed signal separation that includes a soft-input soft-output detector and a soft-input soft-output decoder;
- wherein;
the soft-input soft-output decoder supplies as output logarithmic likelihood ratios (hereinbelow abbreviated as “
LLR”
) for information bit sequences before encoding;
a soft-input soft-output encoder is included that takes these logarithmic likelihood ratios as input and supplies as output logarithmic likelihood ratios for the code word sequence after encoding; and
a priori input of said soft-input soft-output detector is produced based on the output of the soft-input soft-output encoder. - View Dependent Claims (11, 13, 14, 15)
- wherein;
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12. A spatial and temporal iterative decoder in spatial and temporal multiplexed signal separation that includes a soft-input soft-output detector and a soft-input soft-output decoder, wherein:
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said soft-input soft-output decoder supplies as output logarithmic likelihood ratio (hereinbelow abbreviated as “
LLR”
) for information bit sequences before encoding;
a soft-input soft-output encoder is included that takes these logarithmic likelihood ratios as input and supplies as output logarithmic likelihood ratio for codeword sequences after encoding; and
soft replica input of said soft-input soft-output detector is produced based on the output of the soft-input soft-output encoder.
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Specification