Punctured Viterbi decoding method

Error detection/correction and fault detection/recovery – Pulse or data error handling – Digital data error correction

Reexamination Certificate

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Details

C714S790000, C714S795000

Reexamination Certificate

active

06385753

ABSTRACT:

BACKGROUND OF THE INVENTION
1. Field of the Invention
The present invention relates to a punctured Viterbi decoding method for use with a digital mobile communication apparatus or the like.
2. Description of the Related Art
In an information transmission system using a high accuracy decoding method such as the Viterbi decoding method, a punctured process for thinning out convolutional code at a predetermined ratio is performed on the transmission side so as to increase information amount per data transmission unit. When two bits are thinned out from six bits of convolutional code by the punctured process, the information amount per transmission data unit can be increased by 1.5 times.
When convolutional code encoded data that has been punctured-processed is maximum-likelihood decoded by the Viterbi algorithm, regardless of whether a branch metric is generated with or without a punctured data portion, the following decoding process is performed.
In other words, after a decoding process including an ACS calculation is started, a trace-back process is performed from the maximum likelihood state at a predetermined process time point. Decoded data is generated corresponding to the data that is obtained at the traced back time point as a result of calculation. Such a process sequence is successively performed at each process time point so as to obtain required decoded data.
In such a decoding process, if convolutional code encoded data that has been punctured contains many errors, data to be calculated for generating a branch metric corresponding to the punctured data may become inaccurate. Thus, a branch metric value corresponding to the punctured data may become inaccurate. Consequently, the maximum likelihood state obtained as the result of the ACS calculation corresponding to the branch metric value may become inaccurate.
To allow the trace-back process to converge a particular path to a correct path and improve the decoding accuracy, the length of the path memory that performs a trace-back process should be increased. However, when such a path memory is used, the circuit scale becomes large and a high speed clock is required. Alternatively, the process speed decreases.
OBJECTS AND SUMMARY OF THE INVENTION
Therefore, an object of the present invention is to provide a punctured Viterbi decoding method that allows the decoding accuracy to be improved without need to increase the length of the path memory that performs the trace-back process.
The present invention is a punctured Viterbi decoding method that performs maximum-likelihood decoding using the Viterbi algorithm for data that has been generated as a result of an operation that thins out data at predetermined intervals of a convolutional code, comprising the steps of (a) detecting whether or not received data has been thinned out for each decoding process unit composed of a predetermined number of symbols, (b) calculating the value of a branch metric for each decoding process unit corresponding to the received data, (c) performing ACS calculation for calculating values of path metrics for a plurality of states corresponding to the result of step (b), the number of states having been predetermined corresponding to convolutional code encoding process, selecting the maximum likelihood state transition corresponding to the values of the calculated path metrics, and generating path selection information that represents the selected result, (d) performing a trace-back process for generating decoded data corresponding to the values of the path metrics and the path selection information, (e) setting an initial value corresponding to the decoding process unit and prohibiting step (d) when the decoding process unit has been thinned out as the determined result of step (a), and (f) setting an initial value corresponding to the decoding process unit and executing step (d) when the decoding process unit has not been thinned out as the determined result of step (a).
According to the present invention, the trace-back process is prohibited with an initial value that is set corresponding to punctured data.
Since the trace-back process is not performed with an initial value corresponding to punctured data, an incorrect maximum likelihood path corresponding to an error of convolutional code is not used. Consequently, a decoded error can be prevented or suppressed.
These and other objects, features and advantages of the present invention will become more apparent in light of the following detailed description of a best mode embodiment thereof, as illustrated in the accompanying drawings.


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