JP2010073264A - Decoding device and decoding method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To improve decoding performance of a soft input/output. <P>SOLUTION: A branch corresponding to a frame sink part is added to a time-change trellis including a branch of a state changed with passage of time and a branch indicating a stage change, having permitted transition changed with time, and having periodicity. Figure 9 shows a mixed trellis of one time including the branch corresponding to the frame sink part. The mixed trellis has 34 states, the number of branches E including the branch corresponding to the frame sink part is 140. The present invention is applicable to, for example, an optical disk device or the like which decodes a soft input/output. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to a decoding apparatus and a decoding method, and in particular, used for decoding soft input / soft output for decoding input soft value data that is soft value data into output soft value data that is other soft value data. In particular, the present invention relates to a decoding apparatus and a decoding method that are preferable.

  When data is recorded on a recording medium such as a disk, the data is encoded and recorded for error correction or the like.

  FIG. 1 shows an example of a conventional configuration of an optical disc apparatus for recording and reproducing data on an optical disc.

  At the time of data recording, in the optical disc apparatus 10, data to be recorded to be recorded on an optical disc (not shown) is supplied to the Reed-Solomon encoder 11. Here, the data to be recorded is a bit string, and each bit takes a value of 0 or 1.

  The Reed-Solomon encoder 11 encodes data to be recorded into a Reed-Solomon code, and supplies the Reed-Solomon code as a bit string having a value of 0 or 1 to the modulation encoder 12.

  The modulation encoder 12 modulates the Reed-Solomon code from the Reed-Solomon encoder 11 into a modulation code such as a 17PP code (Parity Preserve / Prohibit Repeated Minimum Transition Runlength). Then, a 17PP code as a bit string having a value of 0 or 1 is supplied to an NRZI (Non Return to Zero Inversion) converter 13 as a modulation code obtained as a result of modulation encoding.

  Here, in the optical disc apparatus 10, a modulation code is used in order to perform stable reproduction. As a modulation code, in order to limit the length of pits formed on an optical disc, for example, the number of 0s continuously present between 1 and 1 is limited to d or more and k or less (d, k) An RLL (Run Length Limited) code for limiting or a code capable of controlling a DC (Direct Current) component is used.

  For example, a Blu-ray disc employs a modulation code called a 17PP code. The 17PP code is a code (Run Length Limited Code (1,7)) that restricts (1,7) in which any number of 0 in the range of 1 to 7 appears between 1 and 1, In addition, the modulation code can control the DC component.

  Note that the modulation encoding by the modulation encoder 12 can be performed using, for example, a conversion table in which Reed-Solomon codes and 17PP codes are associated with each other.

  The NRZI converter 13 NRZI converts the 17PP code from the modulation encoder 12 and supplies the NRZI signal obtained as a result to the recording / reproducing system 14. The recording / reproducing system 14 writes the NRZI signal from the NRZI converter 13 in the form of pits on an optical disk (not shown).

  Here, in the NRZI conversion, when the input to the NRZI converter 13 is 0, the immediately preceding output is output as it is as an NRZI signal, and when the input is 1, the immediately preceding output is inverted. Output as NRZI signal.

  Therefore, if the input to the NRZI converter 13 is not a bit string in which at least one 0 is placed between 1 and 1 as in a 17PP code, for example, if 1 is a continuous bit string 11111111, The output of the NRZI converter 13 is a bit string 10101010. Then, pits corresponding to the bit string 10101010 are formed on the optical disc. Note that, based on the pits formed corresponding to the bit string 10101010, the reproduction signal reproduced from the optical disk has an amplitude at which the H (High) level and the L (Low) level are switched in a short cycle corresponding to 1 bit. Therefore, it becomes difficult to detect the signal level of the reproduction signal.

  On the other hand, when the input to the NRZI converter 13 is a 17PP code in which at least one 0 is inserted between 1 and 1, for example, 10101010 in which 1 and 0 are alternately arranged. The output of the NRZI converter 13 is 11001100. Then, pits corresponding to the bit string 11001100 are formed on the optical disc. Based on the pits formed corresponding to the bit string 11001100, the reproduction signal reproduced from the optical disc is a signal with a certain amplitude that switches between the H level and the L level in a certain long period corresponding to 2 bits. Therefore, it becomes easier to detect the signal level of the reproduction signal.

  When the input to the NRZI converter 13 is a bit string in which 0 is continuous over a long period, the reproduction signal reproduced from the optical disk is a signal whose level change is gentle over a long period. In this case, there is a problem that it takes time to lock a PLL (Phase Lock Loop) that generates a clock signal necessary for the operation of each block of the optical disk device 10 or the PLL does not lock. Therefore, the input to the NRZI converter 13 As in the 17PP code, the maximum number of consecutive zeros is also limited to a certain value.

  At the time of data reproduction, in the optical disk apparatus 10 of FIG. 1, the recording / reproducing system 14 reproduces a reproduction signal from the optical disk. The recording / reproducing system 14 includes an A / D (Analog / Digital) converter and an equalizer (not shown), A / D-converts a reproduction signal from the optical disk, and performs processing such as waveform equalization. To output soft data. In addition, the recording / reproducing system 14 has a PLL circuit (not shown), and the PLL circuit generates a clock signal for operating each block of the optical disc apparatus 10 based on the reproduced signal.

  The soft value data output from the recording / reproducing system 14 is supplied to the Viterbi decoder 16.

  Here, in the optical disc apparatus 10 of FIG. 1, a recording / reproducing system 14 for performing recording / reproducing on an optical disc includes a PR (Partial Response) channel such as a PR121 channel, a PR1221 channel, or a PR12221 channel, and an AWGN (Additive White Gaussian Noise) channel. Can be thought of as consisting of

  Therefore, the NRZI signal output from the NRZI converter 13 is added with noise through the PR channel and further through the AWGN channel in the recording / reproducing system 14, and is output as soft value data.

  The PR channel can be expressed by a trellis composed of a state (state) that transitions with time and a branch that represents a transition from a state at a certain time t-1 to a state at the next time t. The channel sys # 11 including the NRZI converter 13 in the PR channel that can be represented by the trellis can also be represented by the trellis. Soft value data read out via a channel that can be represented by a trellis can be decoded into hard value data by maximum likelihood decoding.

  Therefore, the Viterbi decoder 16 decodes the soft value data from the recording / reproducing system 14 into a 17PP code which is hard value data by Viterbi decoding which is one of the maximum likelihood decodings, and supplies it to the modulation decoder 17. To do.

  The modulation decoder 17 uses the conversion table in which the Reed-Solomon code and the 17PP code are associated with each other, for example, the 17PP code that is a bit string of 0 or 1 from the Viterbi decoder 16. The Reed-Solomon code is decoded and supplied to the Reed-Solomon decoder 18.

  The Reed-Solomon decoder 18 converts the Reed-Solomon code, which is a bit string having a value of either 0 or 1, from the modulation decoder 17 into the original data having a value of 0 or 1. Decode to (data to be recorded) and output.

  By the way, as described above, the Viterbi decoder 16 decodes soft-value data into hard-value data, but in recent years, so-called soft-input soft-output that decodes soft-value data into other soft-value data. There is an increasing demand for adopting a soft-input / soft-output decoding device that performs decoding.

  Examples of the implementation algorithm of the soft input / soft output decoding device include a BCJR (Bahl-Cocke-Jeinek-Raviv) algorithm, a Max-Log-BCJR algorithm, and a SW-Max-Log-BCJR algorithm.

  The BCJR algorithm is known as a decoding method that minimizes the symbol error rate after decoding of a convolutional code (see, for example, Non-Patent Document 1). The BCJR algorithm can output the likelihood of each symbol instead of outputting each symbol as a decoding result. Such symbol likelihood output is called soft-output.

  In recent years, research has been conducted to reduce the symbol error probability by making the decoding output of the inner code of the concatenated code and the decoding output of each iteration of the iterative decoding method soft, and decoding such soft output As a decoding method suitable for soft input / soft output decoding, the BCJR algorithm is attracting attention.

  FIG. 2 shows a communication channel model (communication channel model) for explaining the BCJR algorithm. This channel model is composed of a convolutional encoder 21, a memoryless channel 22, and a decoder 23. Digital information (data) is convolutionally encoded and obtained via a memoryless channel (channel) with noise. The received data is decrypted.

That is, the convolutional encoder 21, the input data i _t of the target convolutional coding is supplied. Here, t represents the time, the input data i _t is the time t, the data of the target convolutional coding is supplied to the convolutional encoder 21.

Convolutional encoder 21 performs convolution encoding input data i _t supplied thereto, and outputs the encoded data X _t as convolutional encoding result of the input data i _t. The encoded data X _t passes through the memoryless communication path 22 to be input soft value data Y _t which is soft value data, and is supplied to the decoder 23. The decoder 23, an input soft value data Y _t, decoding the soft-input soft output decoding is performed on the output soft value data lambda _t is a data soft values representing the likelihood of the input data i _t.

  FIG. 3 shows a trellis representing the convolutional encoder 21 of FIG.

Trellis, as described above, is represented by a state S _t a transition with the passage of time, the branch from state S _t-1 of a time t-1 represents a transition to state S _t at the next time t The

  The convolutional encoder 21 includes a shift register (not shown) and performs convolutional encoding using the shift register. The number of trellis states (the number of states at time t) M is determined by the convolutional encoder 21. It is equal to the number of contents that the built-in shift register can take (number of patterns of values stored in the shift register).

In the trellis shown in FIG. 3, the state S _{t-1 at} time t-1 is the state m ′ (m ′ = 0, 1,..., M−1), and at the next time t, the input data i relative _t, is observed coded data X _t, the state S _t at time t is the state m (m = 0,1, ···, M-1) is a transition to.

Here, at time t, the state transition probability p _t (m | m ′) for transitioning from the state m ′ to the state m is expressed by Expression (1).

・・・（１）

... (1)

  Pr {A | B} is a condition under which event B occurs, and represents a conditional probability that event A will occur.

Now, convolutional coding starts from state S ₀ = 0 at time t = 0, and outputs a sequence (time series) X ₁ ^τ = X ₁ , X ₂ ,..., X _τ of encoded data X _t Then, it is assumed that the process ends in the state S _τ = 0 at time t = τ.

Further, the memoryless channel 22 receives the sequence Y ₁ ^τ = Y ₁ , Y ₂ ,..., Y _τ of the input soft value data Y _t with respect to the input of the encoded data (sequence) X ₁ ^τ. It will output.

  Here, the transition probability of the memoryless communication path 22 with noise is defined by a function R (|) satisfying the expression (2) for all times t = 1, 2,.

・・・（２）

... (2)

Here, the function R (Y _j | X _j ) represents the conversion probability that the encoded data X _{j at} time t = _j is converted into the input soft value data Y _j through the memoryless communication path 22. .

The possible values for input data i _t is, for example, when a is 0 or 1, the input soft value data ^{_{(series) Y 1 τ (= Y 1}} , Y 2, ···, Y τ) is observed when it is, the lambda _t (output soft values data is data soft values representing the) likelihood of the input data i _t at time t, when the input soft value data Y ₁ ^tau is observed, the input data i _t is 1 probability Pr | and ^{_{{i t = 1 Y 1 τ}} }, input soft values when data Y ₁ ^tau is observed, the probability input data i _t is _{0 Pr {i t = 0 |} Y ₁ ^τ } and is expressed by Equation (3).

・・・（３）

... (3)

In order to obtain the output soft value data λ _t of Equation (3), the probabilities α _t (m), β _t (m), and γ _t (m ′, m, i) are defined by the following equations.

・・・（４）

... (4)

・・・（５）

... (5)

・・・（６）

... (6)

The probability α _t (m) in the equation (4) is the sequence of input soft value data Y ₁ ^t = from the first time 1 of the entire sequence Y ₁ ^τ of the input soft value data Y _t to a certain time t. When Y ₁ , Y ₂ , ..., Y _t are observed, in the trellis, the probability Pr (S _t = m; Y ₁ ^t } at time t (S _t = m) Hereinafter, this is referred to as a forward probability as appropriate. Pr {A; B} represents the probability that both events A and B occur.

The probability β _t (m) in the equation (5) is a sequence of input soft value data Y _t from a certain time t + 1 to the last time τ of the entire sequence Y ₁ ^τ of the input soft value data Y _{t. +1} ^τ = Y _{t + 1} , Y _{t + 2} , ..., Y _{τ When τ} is observed, the probability that the trellis is in state m at time t (at time t, in state m and then Of the input soft value data Y _{t + 1} ^τ = Y _{t + 1} , Y _{t + 2} ,..., Y _τ ) from time t + 1 to time τ) Pr {Y _{t + 1} ^τ | S _t = m}, hereinafter referred to as a backward probability as appropriate.

The probability γ _t (m ′, m, i) in equation (6) is in the state m ′ at time t−1 and the input data it at the next time _t is a certain value i in the trellis. , A certain input soft value data Y _t is observed, and at time t, the probability of transition to state m (branch metric) Pr {S _t = m; Y _t ; i _t = i | S _t-1 = m '} Yes, hereinafter referred to as output transition probability as appropriate.

The forward probability α _t (m) is calculated from the input soft value data Y ₁ ^t = Y ₁ , Y ₂ ,..., Y _t from the state S ₀ = 0 at the start of encoding (t = 0). Based on the passage probability of each state 0, 1,..., M-1 at time t-1 calculated in time series.

The backward probability β _t (m) is determined from the state S _τ = 0 at the end of encoding (t = τ), and the sequence of input soft value data Y _{t + 1} ^τ = Y _{t + 1} , Y _{t + 2} ,..., Y _τ , corresponding to the passing probability of each state 0, 1,.

Further, output transition probability _{γ t (m ', m,} i) is an input soft value data Y _t at time t, the input data i _t is calculated based on the input probability value i, at time t , Corresponding to the reception probability of the output of each branch of the trellis from the state m ′ to the state m.

FIG. 4 shows the output transition probability γ _t (m ′, m, i) when the number of states M is four.

Here, as described above, since the possible values for input data i _t is 2 kinds of 0 or 1, from one state S _t-1 with a time t-1, at time t the state to S _t There are two ways of transition. Then, since the number M of states is four, from a state S _t-1 at time t-1, how the transition to state S _t at time t, that is, from a state S _t-1 at time t-1 branch to state S _t at the time t is located only ways 8 (= 4 2 types ×), output transition probability _{γ t (m ', m,} i) is the probability of passing through respective branches of the eight To express.

The output soft value data λ _{t in} Expression (3) uses the forward probability α _t (m), the backward probability β _t (m), and the output transition probability γ _t (m ′, m, i). Can be calculated by:

・・・（７）

... (7)

Meanwhile, forward probability alpha _t (m) at time t in equation (4), and its one time before the time t-1 of the forward probability alpha _t-1 (m '), the input data i _t at time t is a value when a i, 'from the output transition probability gamma _t a transition to a state S _t = m at time t (m' state S _t-1 = m at time t-1, m, i) and with, It can be expressed by equation (8).

・・・（８）

... (8)

Here, in the channel model of FIG. 2, as described above, the convolutional coding is started from the state S ₀ = 0 at time t = 0, so the forward probability α ₀ (m) at time t = 0 is And represented by equation (9).

・・・（９）

... (9)

In addition, the backward probability β _t (m) at time t in Expression (5) is the backward probability β _{t + 1} (m ′) at time t + 1 one hour later and the input data i _{t at} time t + 1. _{When +1} is the value i, the output transition probability γ _{t + 1} (m, m ′, i from the state S _t = m at time t to the state S _{t + 1} = m ′ at time t + 1 ) And can be represented by the formula (10).

・・・（１０）

... (10)

Here, in the channel model of FIG. 2, as described above, the convolutional coding ends in the state S _τ = 0 at time t = τ, so the backward probability β _τ (m) at time t = τ is It is represented by Formula (11).

・・・（１１）

(11)

Furthermore, expression output transition probability gamma _t of (6) (m ', m , i) , the time t-1 of state S _t-1 = m' from the state transition to transition to state S _t = m at time t probability p _t (m | m ') and (equation (1)), coded data (state obtained by convolutionally encoding the input data i _t value i S _t-1 = m' from a state S _t = Conversion probability R (Y _t ) in which the encoded data (X) output from the convolutional encoder 21 at the time of transition to m is converted to the input soft value data Y _t at time t through the memoryless communication path 22 | X) is used to express the equation (12).

・・・（１２）

(12)

In the decoder 23 of FIG. 2, the output soft value data λ _t of Expression (7) is obtained according to Expressions (8) to (12).

That is, every time the input soft value data Y _t is received, the decoder 23 obtains the output transition probability γ _t (m ′, m, i) according to the equation (12), and further outputs the output transition probability γ. _{Using t} (m ′, m, i), the forward probability α _t (m) is obtained according to Equation (8) (Equation (9)).

Further, when the decoder 23 receives all of the input soft value data series Y ₁ ^τ , the decoder 23 uses the output transition probability γ _{t + 1} (m ′, m, i) to obtain the equation (10) (equation (11)). Accordingly, the backward probability β _t (m) is obtained.

Then, the decoder 23 performs the forward probability α _t (m) determined for all times t = 1,..., Τ and all states m = 0, 1,. Using the probability β _t (m) and the output transition probability γ _t (m ′, m, i), the output soft value data at all times t = 1,. Find _λt .

According to the BCJR algorithm, the output soft value data λ _t is obtained as described above.

  By the way, in the BCJR algorithm, the calculation amount is large because it includes product calculation. Further, in the BCJR algorithm, since the encoded data needs to end at time t = τ, it is difficult to decode encoded data (continuous data) that lasts longer.

  Therefore, Max-Log-BCJR algorithm and Log-BCJR algorithm have been proposed as methods of soft-input / soft-output decoding that eliminate the product operation and reduce the amount of computation (see, for example, Non-Patent Document 2). In Non-Patent Document 2, the Max-Log-BCJR algorithm is called a Max-Log-MAP algorithm, and the Log-BCJR algorithm is called a log-MAP algorithm.

  As a soft input / soft output decoding method for decoding continuous data, a SW-BCJR algorithm that performs sliding window processing has been proposed (see, for example, Patent Document 1 or Non-Patent Document 3).

  Hereinafter, the Max-Log-BCJR algorithm, the Log-BCJR algorithm, and the SW-BCJR algorithm will be briefly described.

  In the Max-Log-BCJR algorithm, the probability is expressed as a logarithm (natural logarithm) with e being the Napier's constante, and the product of the probabilities is expressed as the sum of logarithms as shown in Equation (13). The calculation is replaced with an arithmetic operation, and the sum operation of the probabilities is approximated by a logarithmic maximum value operation as shown in Expression (14).

・・・（１３）

... (13)

・・・（１４）

(14)

  Note that max (x, y) represents selecting the maximum value among x and y.

Now, α _t ′ (m) in Expression (15) is used as the forward probability (data representing), β _t ′ (m) in Expression (16) is used as the output probability ( Γ _t ′ (m ′, m, i) in the equation (17) is respectively adopted as the data).

・・・（１５）

(15)

・・・（１６）

... (16)

・・・（１７）

... (17)

In this case, the forward probability α _t ′ (m) of Equation (15) can be approximated by Equation (18) by substituting Equation (8) into Equation (15).

・・・（１８）

... (18)

Further, the backward probability β _t ′ (m) of Expression (16) can be approximated by Expression (19) by substituting Expression (10) into Expression (16).

・・・（１９）

... (19)

Furthermore, the output transition probability γ _t ′ (m ′, m, i) of Expression (17) can be expressed by Expression (20) by substituting Expression (12) into Expression (17).

・・・（２０）

... (20)

  Here, in Equation (18) and Equation (19), max for i = 0, 1 (max in which i = 0, 1 is described in the lower part) is the value that follows, and variable i is 0. Represents the selection of the maximum value among the value taken when the variable i is 1 and the value taken when the variable i is 1.

In Expressions (18) and (19), max for m ′ indicates that the subsequent value selects the maximum value among the values taken for the variable m ′ of each value. Incidentally, m 'max of about, m' status as possible values for 0, 1, ..., of the M-1, when there is an input data i _t = i, a transition to state m It is obtained for the state m ′ in which there exists.

Similarly to the equations (15) to (17), if the λ _t ′ of the equation (21) is adopted as the output soft value data, the output soft value data λ _t ′ of the equation (21) By substituting equation (7) into 21), it can be approximated by equation (22).

・・・（２１）

(21)

・・・（２２）

(22)

  Here, in Equation (22), max for m = 0, 1,..., M-1 is the value that follows, when the variable m is 0, 1,. Indicates that the maximum value among the values taken in is selected.

In Expression (22), max for m ′ indicates that the subsequent value selects the maximum value among the values taken for the variable m ′ of each value. Note that max for m ′ in the first term on the right side of the equation (22) is that the input data i _t = 1 in the states 0, 1,..., M−1 as possible values of m ′. When there is a state m ′, a transition to the state m is obtained as a target. Further, 'the max for, m' second term of m states as possible values for 0, 1, ..., of the M-1, when there is an input data i _t = 0, the state It is obtained for a state m ′ where a transition to m exists.

In the decoder 23 of FIG. 2, the output soft value data λ _t of Expression (22) can be obtained using Expressions (18) to (20).

That is, every time the input soft value data Y _t is received, the decoder 23 obtains the output transition probability γ _t ′ (m ′, m, i) according to the equation (20), and further outputs the output transition probability. Using γ _t ′ (m ′, m, i), the forward probability α _t ′ (m) is obtained according to equation (18).

Further, when the decoder 23 receives all of the input soft value data series Y ₁ ^τ , the decoder 23 uses the output transition probability γ _{t + 1} ′ (m ′, m, i) to follow the backward probability according to the equation (19). Find β _t '(m).

The decoder 23 then determines the forward probabilities α _t ′ (m) obtained for all times t = 1,..., Τ and all states m = 0, 1,. Using the backward probability β _t ′ (m) and the output transition probability γ _t ′ (m ′, m, i), the output for all times t = 1,. The soft value data λ _t ′ is obtained.

According to the Max-Log-BCJR algorithm, the output soft value data λ _t ′ is obtained as described above.

  Since the Max-Log-BCJR algorithm does not include product operation, the amount of calculation can be greatly reduced compared to the BCJR algorithm.

By the way, the following equation holds for the logarithm log (e ^x + e ^y ) of the sum operation e ^x + e ^y .

・・・（２３）

... (23)

Since log (1 + e ^{− | xy |} ) on the right side of Expression (23) is a one-dimensional function having | xy | as a variable, each value has a variable | xy | and a variable | xy | function ^{log (1 + e - | xy} |) values (function values) and the association table (hereinafter referred to as function table) if it was prepared, the sum operation e ^x + e ^y logarithm log ( e ^x + e ^y ) can be accurately obtained according to equation (23) using a function table.

  In the Log-BCJR algorithm, the sum operation of the probabilities approximated by Expression (14) in the Max-Log-BCJR algorithm is accurately obtained according to Expression (23).

Therefore, in the Log-BCJR algorithm, compared with the Max-Log-BCJR algorithm, although the amount of calculation of the addition of log (1 + e ^{− | xy |} ) on the right side of Expression (23) increases, Max-Log-BCJR Similar to the algorithm, no product operation is required. Further, the output soft value data λ _t ′ obtained by the equation (22) is obtained by ignoring the quantization error generated when the log (1 + e ^{− | xy |} ) on the right side of the equation (23) is obtained by the function table. Is equal to the value obtained by taking the logarithm of λ _t in Equation (7) obtained by the BCJR algorithm.

  Next, the SW-BCJR algorithm will be described.

In the BCJR algorithm, the backward probability β _t (m) can be obtained only after the entire input soft value data series Y ₁ ^τ has been received, so the encoded data must be terminated at time t = τ. Therefore, it is difficult to decode continuous data.

Therefore, in the SW-BCJR algorithm, as with Viterbi decoding, a truncation length D is introduced, and an initial value is set as an initial value for the backward probability β _t (m) at time t after the truncation length D from time tD. By giving M (1 / M number of states), output soft value data λ _{tD at} time _tD is obtained.

  That is, FIG. 5 is a diagram for explaining the SW-BCJR algorithm.

The SW-BCJR algorithm, the initialization of the forward probability alpha ₀ at time t = 0 '(m) is, for example, like the BCJR algorithm, after performing in accordance with equation (9), an input soft value data Y _t Each time it is received, the following processing is performed, whereby output soft value data is obtained for continuous data.

That is, in the SW-BCJR algorithm, when the input soft value data Y _{t at} time t is received, the output transition probability γ _t (m ′, m, i) is obtained according to the equation (12).

Further, the backward probability β _t (m) is initialized to 1 / M for all states m = 0, 1,..., M−1 without using the equation (11).

Then, the backward probability β _tD (m) of the time (previous time) tD that is temporally backward from the time t by the truncation length D is the output transition probability γ _{t−D + 1} (m ′, m, i), γ _{t-D + 2} (m ', m, i), ..., γ _t (m', m, i) and initial value 1 / M of backward probability β _t (m) Is obtained according to the equation (10).

Furthermore, the backward probability β _tD (m) at time tD, the forward probability α _tD-1 (m) obtained at time tD-1 obtained at time t-1 one time before, and further, by the cutoff length D Using the output transition probability γ _tD (m ′, m, i) at the time tD obtained when the input soft value data Y _tD at the time _tD is received at the time tD, the time tD Output soft value data λ _tD is obtained (FIG. 5).

・・・（２４）

... (24)

Then, using the forward probability α _tD-1 (m) at time _tD-1 and the output transition probability γ _tD (m ′, m, i) at time tD, according to the equation (8), the forward probability at time tD The probability α _tD (m) is obtained. This forward probability α _tD (m) at time tD is calculated by the equation (24) when the input soft value data Y _{t + 1} at the next time _{t + 1} is received. Used to obtain value data λ _{t-D + 1} .

  In Non-Patent Document 3, in addition to the SW-BCJR algorithm, the SW-Log-BCJR algorithm that combines the SW-BCJR algorithm and the Log-BCJR algorithm, and the SW-BCJR algorithm and the Max-Log-BCJR algorithm SW-Max-Log-BCJR algorithm (referred to as SWAL-BCJR algorithm in Non-Patent Document 3) is also described.

  According to the SW-Log-BCJR algorithm and the SW-Max-Log-BCJR algorithm, continuous data can be decoded without product operation.

Hereafter, the same applies to the output transition probability γ _t (m ′, m, i) (γ _t ′ (m ′, m, i) which is the logarithm of γ _t (m ′, m, i)). ) Is simply written as γ. Similarly, the logarithm of the forward probability _{α t (m) (α t} (m) α t took the logarithm of the '(m) as well) and, α and, backward probability _{β t (m) (β t} (m) the same applies to beta _t (m) took, and beta, output soft value data lambda _t a (lambda _t logarithm lambda _t 'similarly taken in), and lambda, described respectively.

WO99 / 62183 pamphlet Bahl, Cocke, Jelinek and Raviv, "Optimal decoding of liner codes for minimizing symbol error rate", IEEE Trans. Inf. Theory, vol. IT-20, pp. 284-287, Mar. 1974 Robertson, Villebrun and Hoeher, "A comparison of optimal and sub-optimal MAP decoding algorithms operating in the log domain", IEEE Int. Conf. On Communications, pp. 1009-1013, June 1995 Benedetto and Montorsi, "Soft-output decoding algorithms in iterative decoding of turbo codes", TDA progress Report 42-124, Feb, 1996

  By the way, there is a time-variant trellis as a target trellis in decoding of soft input / soft output. A time-varying trellis has periodicity with possible transitions varying with time.

That is, for example, in the case of taking one of the values of the input data i _t is 0 or 1, the transition from a certain state, a transition when the input data i _t is 0, the input data i _t there are two transitions and the transition time is 1.

  In the trellis, there is a time-variant trellis that has a periodicity in which possible transitions of two transitions existing for one state change with time.

  In a time-varying trellis, possible transitions (and impossible transitions) among the transitions that exist for a state change with time, so that possible transitions at one time become impossible transitions at other times ( Sometimes a transition that is impossible at one time becomes a transition that is possible at another time).

  Hereafter, in the time-variant trellis, a branch representing a possible transition is referred to as an effective branch and a branch representing an impossible transition is referred to as an invalid branch.

  In addition, since the time-varying trellis has periodicity, among the branches representing transitions existing between a state at a certain time and a state at the next time, an effective branch representing a possible transition (and an impossible transition). A pattern (hereinafter, referred to as a transition pattern as appropriate) taken by an invalid branch representing) appears at a constant period.

  That is, when the time of one period of the time-variant trellis having periodicity is expressed as a period T, between the state of a certain time and the state of the next time from the beginning to the end of the period T, Various transition patterns appear. The transition pattern that appears between the state at time t and the state at the next time t + 1 is between the state at time t + T after the period T and the state at the next time t + T + 1. Appears again (however, it may also appear at a time before the period T elapses).

In the soft input / soft output decoding, the output soft value data λ is obtained from the input soft value data Y _t . For example, the predetermined data such as Expression (18), Expression (19), Expression (22), etc. A certain output transition probability γ is used.

  However, in the time-varying trellis, possible transitions among the transitions that exist for the state, that is, effective branches change with time.

  In the soft input / soft output decoding, if the predetermined calculation for obtaining the output soft value data λ is performed not only on the valid branch but also on the invalid branch, the likelihood of the path passing through the invalid branch is the highest. Therefore, there is a possibility that the performance (accuracy) of decoding of soft input / soft output is deteriorated.

  The present invention has been made in view of such circumstances, and is intended to improve the performance of soft input / soft output decoding.

  A decoding apparatus according to an aspect of the present invention provides input soft value data, which is soft value data obtained by passing encoded data obtained by encoding input data through a channel, to a soft value representing the likelihood of the input data. In a decoding device that decodes output soft value data that is value data, a trellis that includes a state that transitions with the passage of time and a branch that represents the transition of the state, and that represents the channel, and has possible transitions For a time-varying trellis that changes with time and is a trellis having periodicity, a transition represented by the branch is generated based on phase information representing a predetermined timing in one cycle of the time-varying trellis having the periodicity. Used for a predetermined calculation for obtaining the output soft value data from the input soft value data and transition information indicating that the transition is possible or impossible. Storage means for associating and storing data, and calculation means for performing the predetermined calculation using only data of branches representing possible transitions based on the transition information, and the encoded data includes: The time-variant trellis includes a branch corresponding to the frame sync unit.

  The transition information may be transition pattern information indicating which of the plurality of transition patterns existing in one period of the time-varying trellis having the periodicity.

  The time-varying trellis may be a mixed trellis that expresses a modulation code that modulates and encodes the encoded data and a PR channel.

  The PR channel may be a PR121 channel, a PR1221 channel, or a PR12221 channel.

  The modulation code may be a 17PP code.

  The calculation means can perform the predetermined calculation according to the SW-Max-Log-BCJR algorithm.

  A decoding method according to one aspect of the present invention is a method of converting input soft value data, which is soft data obtained by encoding data obtained by encoding input data through a channel, into soft data representing the likelihood of the input data. In a decoding method of a decoding device that decodes output soft value data that is value data, the decoding device includes a state that transitions with time and a branch that represents state transition, and a trellis that represents the channel A time-variant trellis that is a trellis having periodicity that changes depending on time and is generated based on phase information representing a predetermined timing in one period of the time-variant trellis having the periodicity. The output soft value data is obtained from the transition information indicating that the transition represented by the branch is possible or impossible, and the input soft value data. Storing the branch data used in a predetermined calculation in association with each other, and performing the predetermined calculation using only the branch data representing a possible transition based on the transition information, The data has a frame structure composed of a frame sync part and a data part, and the time-varying trellis includes the branch corresponding to the frame sync part.

  In one aspect of the present invention, a trellis that includes a state that transitions with the passage of time and a branch that represents the transition of the state, and that represents a channel, the possible transitions vary with time and have periodicity. For a time-varying trellis that is a trellis, a transition that is generated based on phase information that represents a predetermined timing in one period of the time-varying trellis having the periodicity, and that is capable of transition or impossible that the branch represents Is stored in association with the branch data used for a predetermined calculation for obtaining the output soft value data from the input soft value data. Based on the transition information, possible transitions are stored. The predetermined calculation is performed using only the data of the branches to represent. The encoded data has a frame structure including a frame sync part and a data part, and the time-varying trellis includes the branch corresponding to the frame sync part.

  According to one aspect of the present invention, it is possible to improve soft input / soft output decoding performance.

  Embodiments of the present invention will be described below with reference to the drawings.

  FIG. 6 shows a configuration example of an optical disc apparatus that records and reproduces data on an optical disc and performs decoding of soft inputs and soft outputs at the time of reproduction. The optical disk device 60 is a base of an optical disk device according to an embodiment of the present invention described later with reference to FIG.

  At the time of data recording, data intended for recording on an optical disk (not shown) (data to be recorded) is supplied to the Reed-Solomon encoder 61 in the optical disk device 60.

  Here, the data to be recorded is a bit string, and each bit takes a value of 0 or 1.

  The Reed-Solomon encoder 61 encodes data to be recorded into a Reed-Solomon code, and converts the Reed-Solomon code as a bit string having a value of 0 or 1 to an LDPC (Low Density Parity Check) encoder 62. Supply.

LDPC encoder 62, a Reed-Solomon code from the Reed-Solomon encoder 61 encodes, the resulting, LDPC codes as a bit string that take one of three values 0 or 1, as input data i _t, This is supplied to the modulation encoder 63.

Modulation coder 63, for example, using a conversion table that associates the LDPC code and 17PP code, the input data i _t (LDPC codes) from the LDPC encoder 62, and modulation coding (17PP coding, etc.), The resulting 17PP code as a bit string having a value of 0 or 1 is supplied to the NRZI converter 64.

  The NRZI converter 64 performs NRZI conversion on the 17PP code from the modulation encoder 63 and supplies the resulting NRZI signal to the recording / reproducing system 65. The recording / reproducing system 65 writes the NRZI signal from the NRZI converter 64 in the form of pits on an optical disk (not shown).

At the time of data reproduction, in the optical disk device 60, the recording / reproducing system 65 reproduces a reproduction signal from the optical disk. The recording / reproducing system 65 has an A / D converter, an equalizer, a PLL circuit, etc. (not shown) as in the case of the recording / reproducing system 14 in FIG. Then, processing such as waveform equalization is performed, and soft data Y _t is output. In the PLL circuit built in the recording / reproducing system 65, a clock signal for synchronizing the operation of each component of the optical disk device is generated based on the reproduced signal.

  Soft value data output from the recording / reproducing system 65 is supplied to a SISO (Soft In Soft Out) decoder 67.

  It can be considered that the recording / reproducing system 65 for recording / reproducing data with respect to the optical disc is composed of a PR channel such as a PR121 channel, a PR1221 channel, or a PR12221 channel, and an AWGN channel.

  Therefore, the NRZI signal output from the NRZI converter 64 becomes a signal subjected to intersymbol interference through the PR channel in the recording / reproducing system 65, and further, noise is added through the AWGN channel to add softness. Output as value data.

  By the way, the PR channel can be expressed by a trellis as described above. The channel sys # 21 including the NRZI converter 64 in the PR channel that can be represented by the trellis can also be represented by the trellis.

  In addition, the channel from the input to the output of the modulation encoder 63, that is, in FIG. 6, the modulation code for modulating and coding the LDPC code is an effective branch and an invalid branch, that is, a possible transition changes with time. Can be represented by a time-varying trellis.

  A channel sys # 22 including a modulation encoder 63 that can be expressed by a time-varying trellis in the above-described channel sys # 21 that can be expressed by a trellis can also be expressed by a time-varying trellis.

Soft value data Y _t obtained via (via) the channel sys # 22 that can be expressed by a time-varying trellis can be decoded into hard value data by maximum likelihood decoding. However, in the optical disc apparatus 60, the LDPC encoder 62 is provided immediately after the Reed-Solomon encoder 61. Therefore, it is necessary to decode the LDPC code immediately before decoding the Reed-Solomon code. Therefore, the optical disc apparatus 60 is provided with an LDPC decoder 68 for decoding the LDPC code.

In the decoding of the LDPC code by the LDPC decoder 68, a soft value representing the likelihood of the LDPC code is input (decoding is performed for soft-input). Therefore, the LDPC decoder 68, soft values representing the likelihood of the LDPC code, i.e., here, represents the likelihood of the LDPC code as input data i _t from LDPC encoder 62 to modulator encoder 63 soft value It is necessary to give λ _t as an input.

For this reason, the SISO decoder 67 decodes soft-value data (input soft-value data Y _t ) from the recording / reproducing system 65 into soft-value data to be given to the LDPC decoder 68 at the subsequent stage. The decoded soft output data λ _t is supplied to the LDPC decoder 68. The SISO decoder 67 performs soft input / soft output decoding in accordance with, for example, the SW-Log-BCJR algorithm or the SW-Max-Log-BCJR algorithm.

Here, the SISO decoder 67 corresponds to the decoder 23 in FIG. 2, and the AWGN channel of the recording / reproducing system 65 corresponds to the memoryless communication path 22 in FIG. The channel sys # 22, which is composed of the PR channel of the modulation encoder 63, the NRZI converter 64, and the recording / reproducing system 65 and is expressed by a time-varying trellis, corresponds to the convolutional encoder 21 of FIG. Therefore, the channel sys # 22 is an LDPC code as an input data i _t, can be regarded as an encoder for encoding the encoded data X _t (convolutional encoder).

The LDPC decoder 68 decodes the soft-value data λ _t from the SISO decoder 67 into a Reed-Solomon code that is a bit string having a value of 0 or 1, and supplies the Reed-Solomon decoder 69 with the Reed-Solomon code. .

  The Reed-Solomon decoder 69 converts the Reed-Solomon code, which is a bit string having a value of either 0 or 1, from the LDPC decoder 68 to the original data having a value of 0 or 1 ( Data to be recorded) and output.

  In the optical disc device 60 of FIG. 6, the channel sys # 22 can be represented by a time-varying trellis. Then, as described above, the time-variant trellis representing the channel sys # 22 has a periodicity in which the valid branch and the invalid branch (possible transition and impossible transition) change with time.

  Here, the time-varying trellis will be described.

  FIG. 7 shows an example of a time-varying trellis. This time-varying trellis has four states 0,1,2,3. For each state, there are two transitions, and therefore the number of branches of the time-varying trellis is 8 (= 2 transitions × 4 states).

  That is, in the time-varying trellis of FIG. 7, two branches that represent transitions from state 0 to state 0 and state 1, respectively, two branches that represent transitions from state 1 to state 2 and state 3, respectively, and state 2 to state There are eight branches in total, two branches representing transitions from 0 and state 1 respectively, and two branches representing transitions from state 3 to state 2 and state 3 respectively.

  Furthermore, in the time-varying trellis shown in FIG. 7, among the eight branches that exist for the state, the valid branch and the invalid branch change with time.

  That is, in the time-varying trellis of FIG. 7, for example, in the transition from the state at time t to the state at time t + 1, two of the eight branches representing transitions from state 0 to state 0 and state 1 respectively. The branches are effective branches (indicated by solid arrows in the figure), and the other six branches are invalid branches (indicated by dotted arrows in the figure).

  Further, for example, in the transition from the state at time t + 1 to the state at time t + 2, among the eight branches, two branches representing the transition from state 0 to state 0 and state 1 respectively, and state 1 In total, two branches representing transitions from state 2 to state 2 and state 3 are effective branches, and the other four branches are invalid branches.

  Further, for example, the transition from the state at time t + 2 to the state at time t + 3, the transition from the state at time t + 3 to the state at time t + 4, and the state from time t + 4 to time t + In the transition to the state of 5, in any of the transitions, one of the eight branches represents a transition from the state 0 to the state 1, and two of the transitions from the state 1 to the state 2 and the state 3 respectively. A total of seven branches are active branches, two branches representing transitions from state 2 to state 0 and state 1, respectively, and two branches representing transitions from state 3 to state 2 and state 3 respectively. The other branch (one branch representing a transition from state 0 to state 0) is an invalid branch.

  Also, for example, in the transition from the state at time t + 5 to the state at time t + 6, one of the eight branches that represents the transition from state 0 to state 0, the transition from state 1 to state 2 There are four branches in total, one branch representing the transition from state 2 to state 0, and one branch representing the transition from state 3 to state 2, and so on. The four branches are invalid branches.

  Further, for example, in the transition from the state at time t + 6 to the state at time t + 7, one of the eight branches representing a transition from state 0 to state 0 and from state 2 to state 0 In total, two branches of the one branch representing the transition of the above are valid branches, and the other six branches are invalid branches.

  And the period T of the time-varying trellis in FIG. 7 is 7 time. Therefore, after time t + 8, transition patterns appearing from time t to t + 7 (effective branches representing possible transitions, and Patterns taken by invalid branches representing impossible transitions) repeatedly appear.

  Now, let us say that information indicating that a transition represented by a branch existing in a time-varying trellis is a possible transition or an impossible transition is referred to as transition information. Information can be employed.

  That is, when the transition from the state at time t-1 to the state at time t is referred to as a transition at time t, the branch information is an effective branch for each branch representing the transition at each time. Or, for example, 1-bit information indicating an invalid branch.

  On the other hand, the pattern information is information representing a transition pattern of transition at each time.

  For example, in the time-varying trellis of FIG. 7, the transition pattern of the transition at time t + 1 (transition from the state at time t to the state at time t + 1) is the transition pattern at other times in one cycle (time T). It is different from the transition pattern. Similarly, the transition pattern of the transition at time t + 2, the transition pattern of the transition at time t + 6, and the transition pattern of the transition at time t + 7 are also different from the transition pattern of the transition at other times.

  In addition, the transition pattern of the transition at time t + 3, the transition pattern of the transition at time t + 4, and the transition pattern of the transition at time t + 5 match, but the time t + 3, t + 4, and It is different from the transition pattern of transitions at times other than t + 5.

  Therefore, in the time-varying trellis of FIG. 7, the transition pattern of the transition at time t + 1, the transition pattern of the transition at time t + 2, the transition pattern of the transition at time t + 3 to t + 5, and the time t + 6 There are five types of transition patterns, namely, a transition pattern of the current transition and a transition pattern of the transition at time t + 7.

Use pattern information as transition information, and use the output transition probability γ of only the valid branch and not the output transition probability γ of the invalid branch in the predetermined calculation to obtain the output soft value data λ from the input soft value data Y _t Thus, the decoding performance of soft input / soft output can be improved.

  Next, FIG. 8 shows a configuration example of an optical disc apparatus according to an embodiment of the present invention. As described above, the optical disk device 280 associates and stores the branch output transition probability γ and the transition information of the branch when decoding soft input / soft output when reproducing data from the optical disk. A predetermined calculation for obtaining the output soft value data λ is performed using only the output transition probability γ.

  In the figure, portions corresponding to those of the optical disc apparatus 60 of FIG. 6 are denoted by the same reference numerals, and the description thereof is omitted as appropriate.

  That is, the optical disc apparatus 280 is provided with a Reed-Solomon encoder 61, an LDPC encoder 62, a modulation encoder 63, an NRZI converter 64, a recording / reproducing system 65, an LDPC decoder 68, and a Reed-Solomon decoder 69. Thus, it matches the optical disk device 60 of FIG. The optical disk device 280 is different from the optical disk device 60 in that a phase detector 281 is newly provided and a SISO decoder 282 is provided instead of the SISO decoder 67 of the optical disk device 60. .

A phase detector 281, the input soft value data Y _t is supplied from the recording and reproducing system 65. The phase detector 281 performs, for example, Viterbi decoding of the input soft value data Y _t from the recording / reproducing system 65, thereby, for example, phase information representing a leading timing as a predetermined timing of one period of the time-varying trellis. Is supplied to the SISO decoder 282.

  Here, in the modulation encoder 63, for example, if a 17PP code is adopted as the modulation code, the 17PP code has a frame structure, and the frame is located at the boundary of each frame (1902 bit data portion). A frame sync part representing the head is inserted. The frame sync part is a known 30-bit bit string that cannot be taken by the data part.

  The 17PP code is expressed by a time-varying trellis. In the time-varying trellis expressing the 17PP code, a special transition is performed at the boundary between frames.

  The phase detector 281 detects a frame sync portion representing the start of the frame corresponding to the special transition, and in response to the detection of the frame sync portion, the timing of the start of the frame, in other words, the time-varying trellis For example, a signal that is active only at the head of a 17PP code frame is generated as phase information representing the head timing of one cycle, and is supplied to the SISO decoder 282.

  For example, if the PR channel of the channel sys # 21 is a PR12221 channel, a mixed trellis (PR12221 channel and a PR12221 channel mixed with the PR12221 channel and a 17PP code (including not only the data portion but also the frame sync portion)) The time-varying trellis expressing the 17PP code is as shown in FIG.

  That is, FIG. 9 illustrates the transition of the mixed trellis for one time including the frame sync branch. The mixed trellis of FIG. 9 has 34 states, and the number of branches E is 140 including the branch for the frame sync part.

Further, the output from the PR12221 channel corresponding to the mixed trellis in FIG. 9 is a series of -8, -6, -4, -2, 0, 2, 4, 6, 8 as shown in FIG. Since one time of the mixed trellis in FIG. 9 corresponds to three outputs of the PR12221 channel, one frame is expressed by 644 (= 1932/3) time. That is, this mixed trellis has a period T of 644 times. The number of pattern information (pattern number P) as transition information is 15.

  10 to 12 represent the mixed trellis of FIG. 9 as a numerical table. 10 to 12, the values in parentheses of the current state and the next state indicate the state of the 17PP code on the left side and the state of the PR12221 channel on the right side. The valid transition pattern number represents which transition pattern is valid (invalid) among the 15 types of transition patterns existing in the period T.

  For example, the branch with the branch number 1 is a branch that transitions from the current state (0,1) to the next state (1,7), and among the 15 types of patterns, 8, 9, 10, 11, 12, 13 , 14 transition patterns are valid branches (0, 1, 2, 3, 4, 5, 6, 7 transition patterns are invalid branches).

  Also, for example, the branch with branch number 2 is a branch that transitions from the current state (0,1) to the next state (0,8), and among the 15 types of patterns, 0, 7, 8, 9, 10, This indicates that the transition pattern of 11, 12, 13, and 14 is an effective branch (the transition pattern of 1, 2, 3, 4, 5, and 6 is an invalid branch).

  Further, for example, the branch with the branch number 19 is a branch that transitions from the current state (1,0) to the next state (1,0), and is an effective branch in 3 transition patterns among 15 types of patterns ( 0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14).

  Note that, for example, ten branches with an * (asterisk) added to the branch number, such as branch numbers 19 and 50, are branches corresponding to the frame sync unit.

  FIGS. 14 to 16 show transition patterns of time-varying trellises (mixed trellises) for one frame (644 times). Of the time-varying trellis for 644 times, time 0 to time 9 corresponds to the frame sync part, and time 10 to time 643 corresponds to the data part.

  Specifically, transition pattern 0 at time 0, transition pattern 1 at time 1, transition pattern 2 at time 2, transition pattern 3 at time 3, transition pattern 4 at time 4, transition pattern at time 5 2, transition pattern 3 at time 6, and transition pattern 5 at time 7.

  Also, transition pattern 6 at time 8, transition pattern 7 at time 9, transition pattern 8 at time 10, transition pattern 9 at time 11, transition pattern 10 at time 12, transition pattern from time 13 to time 640 11

  Furthermore, the transition pattern 12 is obtained at time 641, the transition pattern 13 is obtained at time 642, and the transition pattern 14 is obtained at time 643.

  Returning to FIG. The SISO decoder 282 associates the transition information generated based on the phase information supplied from the phase detector 281 with the branch output transition probability γ used in the predetermined calculation for obtaining the output soft value data λ. Based on the transition information, using only the output transition probability γ corresponding to the valid branch, for example, the SW-Max-Log-BCJR algorithm performs a predetermined calculation to obtain the output soft value data λ, and the result The obtained output soft value data λ is supplied to the LDPC decoder 68.

  That is, the SISO decoder 282 displays transition information indicating that the transition represented by each branch existing in the time-variant trellis to be subjected to soft-input / soft-output decoding is possible transition or impossible transition, for example, The transition pattern is stored for each time of period T with reference to the first time (timing) of one period of the time-varying trellis.

Then, at time t after time ΔT from the time when phase information is supplied from the phase detector 281, the SISO decoder 282 calculates an equation from the input soft value data Y _t supplied from the recording / reproducing system 65 at time t. According to (20), the output transition probability γ at time t (the output transition probability γ of the branch representing the transition from the state at time t-1 to the state at time t) is obtained for all branches existing in the time-varying trellis. The output transition probability γ and the transition information for time t are stored in association with each other.

  Further, the SISO decoder 282 performs calculation of Expression (18), Expression (19), and Expression (22) using the output transition probability γ corresponding to the valid branch based on the transition information, and outputs the soft output value. Data λ is obtained and supplied to the LDPC decoder 68.

  Next, processing performed by the SISO decoder 282 in FIG. 8 to store the output transition probability γ and transition information at time t in association with each other will be described in detail with reference to FIG. However, for the sake of simplicity of explanation, a time-variant trellis in which eight branches exist for four states, similar to the example of FIG. 7, will be described as an example.

  The left part of FIG. 17 shows a part of the time-varying trellis, that is, the part of the time-varying trellis of FIG. 7 from the state at time t + 6 to the state at time t + 7. Branch information and pattern information are shown as transition information.

When the input soft value data Y _{t + 7} at time t + ₇ is supplied from the recording / reproducing system 65 (FIG. 8), the SISO decoder 282 is in the state m ′ at time t + 6 and the next time. When the input data i _{t + 7 of t + 7} is 0 or 1, the input soft value data Y _{t + 7} is observed, and the output transition probability γ _{t + 7} (m ′, m, 1) and γ _{t + 7} (m ', m, 0) (more precisely, γ _{t + 7} ' (m ', m, 1) and γ _{t + 7} ' (m ', m, 0)) Is calculated according to equation (20).

  Here, in the time-varying trellis, as described with reference to FIG. 7, two branches representing transitions from state 0 to state 0 and state 1 respectively, and two branches representing transitions from state 1 to state 2 and state 3 respectively. There are eight branches in total: two branches representing transitions from state 2 to state 0 and state 1, respectively, and two branches representing transitions from state 3 to state 2 and state 3, respectively.

Then, for example, at time t + 6, state 0 Niite, when the input data i _t is a value of 0 or 1, respectively, transition to state 0 or state 1, state 1 Niite, input data i _t when there was a value of 0 or 1, respectively, transition to state 2 or state 3, when the state 2 Niite, input data i _t is a value of 0 or 1, respectively, in the state 0 or state 1 transition to state 3 Niite, when the input data i _t is a value of 0 or 1, and making a transition to the state 2 or 3.

In this case, in the SISO decoder 282, as shown in the left of FIG. 17 (in the left of FIG. 17, the suffix t + 7 representing the time of γ _{t + 7} (m ′, m, i) is omitted) state 0 Niite, input data i _t is 0, output transition probability gamma _{t + 7} branches 0 → 0 transition to state 0 (0,0,0), state 0 Niite, input data i _t is a value 1, output transition probability gamma _{t + 7} branches 0 → 1 that represents a transition to state 1 (0,1,1), state 1 Niite, input data i _t is equal to 0, to state 2 branches represent the transitions 1 → 2 output transition probability γ _{t + 7} (1,2,0), state 1 Niite, input data i _t is equal to 1, the branch 1 → 3 representing a transition to state 3 output transition probability γ _{t + 7} (1,3,1), state 2 Niite, input data i _t is 0, output transition probability gamma _{t + 7} branches 2 → 0 which represents the transition to state 0 (2,0,0), state 2 Niite, input data i _t is the value 1, the output transition probability gamma _{t + 7} branches 2 → 1 that represents a transition to state 1 (2,1,1), In state 3, input Over data i _t is 0, branches 3 → 2 output transition probability γ _{t + 7} (3,2,0) representing the transition to state 2, and state 3 Niite, input data i _t value 1 and the output transition probability γ _{t + 7} (m ′, m, m) of each of the eight branches of the output transition probability γ _{t + 7} (3,3,1) of the branch 3 → 3 representing the transition to the state 3 i) is required.

  In addition, the SISO decoder 282 obtains transition information of the transition from the state at time t + 6 to the state at time t + 7.

  Here, as described in FIG. 7, in the time-varying trellis, in the transition from the state at time t + 6 to the state at time t + 7, the transition from state 0 to state 0 among the eight branches is performed. In total, two branches are the valid branches, and the other six branches are invalid branches.

  When pattern information is adopted as the transition information, the SISO decoder 282 uses the transition information of the transition from the state at time t + 6 to the state at time t + 7 as described in FIG. (Transition pattern number) 2 representing.

In the SISO decoder 282, the output transition probability γ _{t + 7} (0,0,0) of the branch 0 → 0, the output transition probability γ _{t + 7} (0,1,1) of the branch 0 → 1, and the branch 1 → 2 output transition probability γ _{t + 7} (1,2,0), branch 1 → 3 output transition probability γ _{t + 7} (1,3,1), branch 2 → 0 output transition probability γ _{t + 7} (2,0,0), branches 2 → 1 of the output transition probability gamma _{t + 7} (2,1,1), branches 3 → 2 output transition probability γ _{t + 7} (3,2,0), and, Eight branch output transition probabilities of branch 3 → 3 output transition probability γ _{t + 7} (3,3,1) and value (transition pattern number) 2 representing pattern information are stored in association with each other. The

  Next, processing of the SISO decoder 282 will be described.

In the SISO decoder 282, as the branch data used for the calculation of the equations (18), (19), and (22) as the predetermined calculation for obtaining the output soft value data λ from the input soft value data Y _t . The output transition probability γ is obtained and stored each time the input soft value data Y _t is supplied, and the forward transition probability α of Expression (18) is stored using the storage process of the output transition probability γ and the stored output transition probability γ. The backward probability β in equation (19) and the output soft value data λ in equation (22) are calculated, and the forward probability α, backward probability β, and output soft value data λ are calculated.

  First, the storage process by the SISO decoder 282 will be described with reference to the flowchart of FIG.

In the storage process, when the input soft value data Y _t is supplied from the recording / reproducing system 65 (FIG. 8) to the SISO decoder 282, the SISO decoder 282 receives the input from the recording / reproducing system 65 in step S131. By calculating the equation (20) using the soft value data Y _t , the output transition probability γ of the E branches of the time-varying trellis as described above is calculated and supplied to the γRAM control unit 402.

  In step S131, the SISO decoder 282 increments the count value of the built-in counter by one. Note that this counter resets the count value to 0 when active phase information is received from the phase detector 281 (FIG. 8).

  Thereafter, the process proceeds from step S131 to step S132, and the SISO decoder 282 converts the count value of the counter into transition pattern information, so that the E transitions for which the output transition probability γ has been obtained in the immediately preceding step S131 are obtained. Transition pattern information about the branch of is generated.

  In step S133, the SISO decoder 282 associates the output transition probability γ of the E branches with the transition pattern information about the E branches, and outputs the transition probability γ of the E branches and the transition pattern information. And remember the set.

Thereafter, every time the input soft value data Y _t is supplied from the recording / reproducing system 65 (FIG. 8) to the SISO decoder 282, the processes of steps S131 to S133 are performed.

Next, calculation processing by the SISO decoder 282 will be described with reference to the flowchart of FIG.
In step S141, the SISO decoder 282 reads the set of output transition probabilities γ and transition pattern information of E branches stored in step S133 described above.

  In step S142, the SISO decoder 282 converts the read pattern information into branch information of E branches. In step S143, the SISO decoder 282 uses the output transition probability γ of only the valid branch among the output transition probabilities γ of the E branches based on the branch information of the E branches as the converted transition information. Then, a predetermined calculation is performed.

That is, among the output transition probabilities γ of E branches, using the output transition probability γ of only the effective branch and the forward probability α of time t _α -1 one time before obtained previously is given by the equation (18). is carried out of the calculation, the forward probability α of time t _α is required.

Further, among the output transition probabilities γ of E branches, using the output transition probability γ of only the effective branch and the backward probability β at time t _β1 +1 one hour after the previous time, the equation (19) Is calculated, and the backward probability β at time t _β1 is obtained.

Further, among the output transition probabilities γ of the E branches, using the output transition probability γ of only the effective branch and the backward probability β of the time t _β2 +1 one hour after the previous time, Expression (19) The backward probability β at time t _β2 is obtained.

  Further, using the output transition probability γ of only the effective branch of the output transition probabilities γ of E branches, the forward probability α previously determined, and the backward probability β, the calculation of Expression (22) is performed. The output soft value data λ is obtained.

Thereafter, each time, that is, whenever the input soft value data Y _t is supplied from the recording / reproducing system 65 (FIG. 8) to the SISO decoder 282, the processes of steps S141 to S143 are performed.

  As described above, the SISO decoder 282 stores the pattern information as the transition information and the output transition probability γ in association with each other, and uses the output transition probability γ of only the valid branch based on the transition information. Since the equations (18), (19), and (22) for obtaining the value data λ are calculated, the output transition probability γ of the invalid branch in the time-varying trellis is used for the predetermined calculation for obtaining the output soft value data λ. It is prevented from being used, and as a result, the decoding performance of soft input / soft output can be improved.

  The embodiment of the present invention is not limited to the above-described embodiment, and various modifications can be made without departing from the gist of the present invention.

  That is, the SISO decoder 282 can perform soft input / soft output decoding in accordance with, for example, the SW-Log-BCJR algorithm in addition to the SW-Max-Log-BCJR algorithm.

In the present embodiment, the input soft value data Y _t obtained from the optical disc is decoded into the output soft value data λ _t , but the present invention is applied to the input soft value data obtained from a recording medium such as an optical disc. another case of decoding the value data Y _t to output soft values data lambda _t, for example, when decoding an input soft value data Y _t that has been transmitted via a wireless or wired transmission medium to the output soft value data lambda _t It can also be applied to.

It is a block diagram which shows the structure of an example of the conventional optical disk apparatus. It is a figure which shows the model of the communication path explaining a BCJR algorithm. FIG. 3 shows a trellis representing the convolutional encoder of FIG. In a case where the number M of states is four, which is a diagram showing an output transition probability _{γ t (m ', m,} i). It is a figure explaining SW-BCJR algorithm. It is a block diagram which shows the structural example of the optical disk apparatus which performs soft input soft output decoding. It is a figure which shows a time-variable trellis. 1 is a block diagram illustrating a configuration example of an optical disc device to which the present invention is applied. It is a figure which shows the mixed trellis for 1 time including the branch corresponding to a frame sync part. It is a figure which shows the output of the mixing trellis of FIG. It is a figure which shows the transition pattern number from which each branch of the mixed trellis of FIG. 9 becomes effective. It is a figure which shows the transition pattern number from which each branch of the mixed trellis of FIG. 9 becomes effective. It is a figure which shows the transition pattern number from which each branch of the mixed trellis of FIG. 9 becomes effective. It is a figure which shows the transition pattern for 1 period of the mixed trellis of FIG. It is a figure which shows the transition pattern for 1 period of the mixed trellis of FIG. It is a figure which shows the transition pattern for 1 period of the mixed trellis of FIG. FIG. 9 is a diagram illustrating a process of storing an output transition probability γ and transition information at time t in association with each other, performed by the SISO decoder of FIG. 8. It is a flowchart explaining the memory repair by the SISO decoder of FIG. It is a flowchart explaining the calculation repair by the SISO decoder of FIG.

Explanation of symbols

  21 convolutional encoder, 22 memoryless channel, 23 decoder, 61 Reed-Solomon encoder, 62 LDPC encoder, 63 modulation encoder, 64 NRZI converter, 65 recording / reproducing system, 67 SISO decoder, 68 LDPC decoder 69 Reed-Solomon decoder, 281 phase detector, 282 SISO decoder

Claims (7)

Decodes input soft value data, which is soft value data obtained by encoding data encoded through the channel, into output soft value data, which is soft value data representing the likelihood of the input data. In the decoding device
A time-variant trellis that consists of a state that transitions with the passage of time and a branch that represents a state transition, and that expresses the channel, where the possible transition changes with time and is a trellis having periodicity. Transition information generated based on phase information indicating a predetermined timing in one period of the time-varying trellis having the periodicity, indicating that the transition represented by the branch is possible or impossible. When,
Storage means for associating and storing the branch data used in a predetermined calculation for obtaining the output soft value data from the input soft value data;
Calculation means for performing the predetermined calculation using only data of branches representing possible transitions based on the transition information; and
The encoded data has a frame structure including a frame sync part and a data part,
The time-varying trellis includes the branch corresponding to the frame sync unit. The transition information is the transition pattern information indicating which of the plurality of transition patterns exists in one period of the time-varying trellis having the periodicity. Decoding device. The decoding apparatus according to claim 2, wherein the time-varying trellis is a mixed trellis that expresses a modulation code that modulates and encodes the encoded data and a PR (Partial Response) channel. The decoding apparatus according to claim 3, wherein the PR channel is a PR121 channel, a PR1221 channel, or a PR12221 channel. The decoding apparatus according to claim 3, wherein the modulation code is a 17PP code (Parity Preserve / Prohibit Repeated Minimum Transition Runlength). The decoding device according to claim 2, wherein the calculation means performs the predetermined calculation according to a SW-Max-Log-BCJR algorithm. Decodes input soft value data, which is soft value data obtained by encoding data encoded through the channel, into output soft value data, which is soft value data representing the likelihood of the input data. In the decoding method of the decoding device,
The decoding device is
A time-variant trellis that consists of a state that transitions with the passage of time and a branch that represents a state transition, and that expresses the channel, where the possible transition changes with time and is a trellis having periodicity. Transition information generated based on phase information indicating a predetermined timing in one period of the time-varying trellis having the periodicity, indicating that the transition represented by the branch is possible or impossible. When,
Used in a predetermined calculation for obtaining the output soft value data from the input soft value data, and storing the branch data in association with each other;
Based on the transition information, using only branch data representing possible transitions, and performing the predetermined calculation,
The encoded data has a frame structure including a frame sync part and a data part,
The time-varying trellis includes the branch corresponding to the frame sync unit.

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