CN1777044B - State metric bit wide control method and device for Turbo code decoder - Google Patents

Abstract

The method makes all measured state values positive generated from forward directed and inverted recursion procedures of MAP decoding algorithm for Turbo codes. Thus, simple normalizing operation can be adopted to reduce bit width of measured state value. Moreover, implementation of hardware is simpler according the measured state values calculated by the disclosed method. When calculating measured path values through forward directed and inverted recursion procedures, the method adds specific offset to the calculation so that all measured path values obtained are positive. Using minimal value in all measured path values in current moment carries out normalization for all measured path values. Advantages are: reducing bit width of measured state values without influence on performance of decoder of Turbo code; reducing area of chip. The invention also lowers complexity of hardware for realizing recursion procedures.

Description

Be used for Turbo code decoder state metric bit wide control method and device

Technical field

The present invention relates to a kind of Turbo code decoder state metric bit wide control method and device of being used for.

Background technology

The principle of Turbo code is based on the algorithm of traditional cascaded code and the correction of structure, and the introducing of interleaver makes the positive feedback of iterative decoding obtain good elimination.The Turbo code encoder is made up of two recursive systematic convolutional codes (recursive systematic convolutional code is called for short the RSC sign indicating number), interleaver and canceller.Figure one has provided the structure of Turbo code encoder in the cdma2000.According to the difference of canceller punching (puncture) form, the encoder bit rate of this Turbo code can change between 1/6 to 1/2.Take all factors into consideration from decoder implementation complexity and decoding performance, Turbo code generally adopts maximum a posteriori probability (maximum a posteriori the is called for short MAP) decoding algorithm of iteration form to decipher.Because the computational complexity of MAP algorithm is higher, derived the MAP algorithm that two classes are simplified recently again, be respectively Log-MAP algorithm and Max-Log-MAP algorithm.Figure two has provided classical Turbo code iterative decoder structure chart.The Turbo code decoder is by two decoders based on the soft input of MAP algorithm, soft output (soft-input soft-output decoder, be called for short the SISO decoder), interleaver and deinterleaver constitute, through alternately decoding, soft output repeatedly obtain decoding behind iterative decoding, the zero passage hard decision and exports to input signal.

The complexity of Turbo code decoding algorithm is mainly by the decision of its SISO decoder, because soft input, soft output decoding algorithm relate to real arithmetic, and more complicated, and need iteration repeatedly, cause and realize the larger of circuit, and throughput is lower.Below the most basic MAP algorithm is simply introduced:

Suppose that the soft of two SISO decoders is output as:

${\mathrm{\Λ}}_1\left(d_k\right)=\log \frac{P\{d_k=1/R_1^N\}}{P\{d_k=0/R_1^N\}}---\left(1\right)$

Wherein, d _kWhat represent is k bit in the noncoded information bit sequence, $R_1^N=(x_1^N,y_{1k1}^N)$ Or (x ₁ ^N, y _2k1 ^N) that represent is the information bit sequence x that receives ₁ ^NWith two check bit sequences y _1k1 ^NOr y _2k1 ^N, be respectively applied for two SISO decoders, Λ ₁(d _k) that represent is d _kLog-likelihood probability (logarithmlikelihood ratio, be called for short LLR).

Through deriving Λ ₁(d _k) can be expressed as follows form:

$\mathrm{\Λ}\left(d_k\right)=\frac{\underset{m}{\mathrm{\Σ}}\underset{m^{\′}}{\mathrm{\Σ}}{\mathrm{\γ}}_1(R_k,m^{\′},m){\mathrm{\α}}_{k-1}\left(m^{\′}\right){\mathrm{\β}}_k\left(m\right)}{\underset{m}{\mathrm{\Σ}}\underset{m^{\′}}{\mathrm{\Σ}}{\mathrm{\γ}}_0(R_k,m^{\′},m){\mathrm{\α}}_{k-1}\left(m^{\′}\right){\mathrm{\β}}_k\left(m\right)}---\left(2\right)$

Wherein, m and m ' represent the k moment and k-1 coder state (S constantly respectively _kAnd S _K-1);

${\mathrm{\α}}_k\left(m\right)=P\{S_k=m,R_1^k\}=\underset{m^{\′}}{\mathrm{\Σ}}\underset{i}{\mathrm{\Σ}}{\mathrm{\γ}}_i(R_k,m^{\′},m){\mathrm{\α}}_{k-1}\left(m^{\′}\right)---\left(3\right)$

Expression forward path tolerance (forward path metric);

${\mathrm{\β}}_k\left(m\right)=P\{R_{k+1}^N/S_k=m\}=\underset{m^{\′}}{\mathrm{\Σ}}\underset{i}{\mathrm{\Σ}}{\mathrm{\γ}}_i(R_{k+1},m,m^{\′}){\mathrm{\β}}_{k+1}\left(m^{\′}\right)---\left(4\right)$

Expression reverse path tolerance (backward path metric);

γ _i(R _k，m′，m)＝P{d _k＝i，S _k＝m，R _k/S _k-1＝m′} (5)

Expression branch metric (branch metric).

Consider the compromise of implementation complexity and Turbo code decoder performance, what often adopt in actual the realization is the Max-Log-MAP algorithm, adopts log (e ^a+ e ^b(a b) simplifies the MAP algorithm to)=max.Adopt the Max-Log-MAP algorithm, find the solution the index, the logarithm operation that need in preceding, reverse path tolerance and the branch metric formula and become the add operation of simple linearity and asked and be worth computing most, significantly reduced the complexity of decoding.

From (3) and (4) as can be seen, preceding, reverse path tolerance all calculates by recursion, and each will calculate the α and the β value of M state.Because tolerance constantly adds up, do not do normalized if do not consider each step, even the needed quantizing bit number of initial time α and β is also few, but through a lot of backs (the longest frame length of WCDMA and TD-SCDMA system Turbo code is 5114) of adding up that go on foot, very long (, will increase by 13 bits) that bit wide will become for WCDMA and TD-SCDMA system, thus need a large amount of chip areas, and arithmetic speed is greatly affected, reduces the decoding rate of Turbo code decoder.Therefore, consider the hardware implementation complexity and the resource consumption of Turbo code decoder, require the shared bit wide of α and β value few more good more.But, in order to guarantee the performance of Turbo code decoder, quantizing bit number to computing must have certain requirement, be that figure place in the computing can not be very little, otherwise the forward and backward path metric is overflowed, the decoding performance of deterioration Turbo code greatly, this just with between realization scale and the arithmetic speed contradicts.

Summary of the invention

A kind of Turbo code decoder state metric bit wide control method and device of being used for that invention provides can not influence under the situation of Turbo code decoder performance substantially, reduces the needed bit width of forward and backward path metric.

In order to achieve the above object, the invention provides a kind of Turbo code decoder state metric bit wide control method that is used for, comprise:

Initial forward path metric and back are to the calculation procedure of path metric;

The side-play amount calculation procedure;

Initial forward path tolerance and back are to path metric and offset addition step;

Current forward path tolerance and current back minimum value statistic procedure to path metric; And

Utilize above-mentioned current forward path tolerance and current back minimum value, normalized step is carried out to path metric in current forward path tolerance and back to path metric.

The corresponding Turbo code decoder state measurement bit-width control device that is used for comprises:

Initial forward path metric and back are to the calculation element of path metric;

The side-play amount calculation element;

Initial forward path tolerance and back are to the adder of path metric and offset addition;

Current forward path tolerance and current back minimum value selector of adding up to the minimum value of path metric; And

Utilize above-mentioned current forward path tolerance and current back minimum value, normalized subtracter is carried out to path metric in current forward path tolerance and back to path metric.

A kind of Turbo code decoder state metric bit wide control method and device of being used for provided by the invention, result of calculation after each step computing in preceding, the reverse path metric calculation is controlled in the very limited scope, thereby make the computing figure place descend greatly, and this method for normalizing computing can be simplified the complexity of computing so that participating in all variablees of computing all is positive number.

Description of drawings

Fig. 1 is the Turbo code encoder of cdma2000 in the background technology;

Fig. 2 is a Turbo code iterative decoder in the background technology;

Before Fig. 3 adopts Turbo code after the inventive method, the flow chart of reverse path metric calculation;

Fig. 4 adopts the present invention that α and β are handled the ber curve that adopts enough bit wides with α and β for when the Turbo code frame length is 1280;

Fig. 5 adopts the present invention that α and β are handled the frame error rate curve that adopts enough bit wides with α and β for when the Turbo code frame length is 1280.

Embodiment

Followingly specify preferred forms of the present invention according to Fig. 3～Fig. 5:

The invention provides a kind of Turbo code decoder state metric bit wide control method and device of being used for, it comprises following steps:

Step 1, preceding reverse path metric calculation device utilize Max-Log-MAP algorithm computation initial forward path metric and back to path metric:

${\widehat{\mathrm{\α}}}_k\left(m\right)=\log \left[{\mathrm{\α}}_k\left(m\right)\right]==\underset{m^{\′}}{\max }(\frac{x_k{u}_k^i+y_k{v}_k^{i,m^{\′}}}{{\mathrm{\σ}}^2}+F\left(z_k\right)+{\widehat{\mathrm{\α}}}_{k-1}\left(m^{\′}\right))---\left(6\right)$

${\widehat{\mathrm{\β}}}_k=\log \left[{\mathrm{\β}}_k\left(m\right)\right]=\underset{m^{\′}}{\max }(\frac{x_{k+1}{u}_{k+1}^i+y_{k+1}{v}_{k+1}^{i,m^{\′}}}{{\mathrm{\σ}}^2}+F\left(z_{k+1}\right)+{\widehat{\mathrm{\β}}}_{k+1}\left(m^{\′}\right))---\left(7\right)$

Wherein, $F\left(z_k\right)=\left\{\begin{array}{cc}{z}_k-\max (0,z_k)& d_k=1\\ -\max (0,z_k)& d_k=0\end{array}\right.$ K bit d of expression _kEqual 0 or 1 prior probability, z _kThe outer cover letter breath that expression upper level SISO decoder produces, $u_k^i=1-2\×x_k,$ $v_k^{i,m}=1-2\×y_k$ Represent binary phase shift keying modulation (being called for short BPSK) or Quadrature Phase Shift Keying modulation (being called for short QPSK) modulation respectively down, the information symbol sequence and the checking symbol sequence of the output of Turbo code encoder.

Because the initial condition and the final state of rsc encoder all are 0 in the Turbo code encoder, so the initial value of the initial value of forward path tolerance and reverse path tolerance is as follows:

${\widehat{\mathrm{\α}}}_0\left(m\right)=\left\{\begin{array}{cc}\∞& m=0\\ 0& m\≠0\end{array}\right.---\left(8\right)$

${\widehat{\mathrm{\β}}}_N\left(m\right)=\left\{\begin{array}{cc}\∞& m=0\\ 0& m\≠0\end{array}\right.---\left(9\right)$

Step 2, calculating side-play amount:

Step 2.1, comparator are according to F (z in formula (6) and (7) _k), obtain (z with respect to prior probability F _k) side-play amount z _Koffset:

z _koffset＝max(|z _k-max(0，z _k)|，|-max(0，z _k)|) (10)

The information bit x that step 2.2, comparator are imported according to the Turbo code decoder _kWith check bit y _kObtain side-play amount xy with respect to the decoder input signal _Koffset:

xy _koffset＝2×max(|x _k/σ ²|，|y _k/σ ²|) (11)

Step 3, adder add side-play amount with initial forward path tolerance and back to path metric, and obtaining current forward path tolerance and back all is positive number to path metric:

${\widehat{\mathrm{\α}}}_k\left(m\right)=\log \left[{\mathrm{\α}}_k\left(m\right)\right]=\underset{m^{\′}}{\max }(\frac{x_k{u}_k^i+y_k{v}_k^{i,m^{\′}}}{{\mathrm{\σ}}^2}+F\left(z_k\right)+{\widehat{\mathrm{\α}}}_{k-1}\left(m^{\′}\right))+z_{\mathrm{offset}}+{\mathrm{xy}}_{\mathrm{offset}}---\left(12\right)$

${\widehat{\mathrm{\β}}}_k\left(m\right)=\log \left[{\mathrm{\β}}_k\left(m\right)\right]=\underset{m^{\′}}{\max }(\frac{x_{k+1}{u}_{k+1}^i+y_{k+1}{v}_{k+1}^{i,m^{\′}}}{{\mathrm{\σ}}^2}+F\left(z_{k+1}\right)+{\widehat{\mathrm{\β}}}_{k+1}\left(m^{\′}\right))+z_{\mathrm{offset}}+{\mathrm{xy}}_{\mathrm{offset}}---\left(13\right)$

Step 4, minimum value selector are added up all current forward path tolerance α and current back minimum value to path metric β: α _MinAnd β _Min

Step 5, subtracter utilize α _MinAnd β _MinCurrent forward path tolerance and back are carried out the normalization operation to path metric:

${\widehat{\mathrm{\α}}}_k\left(m\right)=\log \left[{\mathrm{\α}}_k\left(m\right)\right]$

$=\underset{m^{\′}}{\max }(\frac{x_k{u}_k^i+y_k{v}_k^{i,m^{\′}}}{{\mathrm{\σ}}^2}+F\left(z_k\right)+{\widehat{\mathrm{\α}}}_{k-1}\left(m^{\′}\right))+z_{\mathrm{offset}}+{\mathrm{xy}}_{\mathrm{offset}}-{\mathrm{\α}}_{\min }---\left(14\right)$

${\widehat{\mathrm{\β}}}_k\left(m\right)=\log \left[{\mathrm{\β}}_k\left(m\right)\right]$

$=\underset{m^{\′}}{\max }(\frac{x_{k+1}{u}_{k+1}^i+y_{k+1}{v}_{k+1}^{i,m^{\′}}}{{\mathrm{\σ}}^2}+F\left(z_{k+1}\right)+{\widehat{\mathrm{\β}}}_{k+1}\left(m^{\′}\right))+z_{\mathrm{offset}}+{\mathrm{xy}}_{\mathrm{offset}}-{\mathrm{\β}}_{\min }---\left(15\right)$

Specific embodiment:

The input data bit width of WCDMA system Turbo code decoder is 6 bits, and the outer cover letter breath bit wide that the SISO decoder produces is 10 bits.If do not adopt normalization algorithm of the present invention, the needed bit wide of forward and backward path metric is at least 24 bits, can not overflow in the time of could guaranteeing to calculate α and β.If adopt normalization algorithm provided by the present invention, simulation result shows, just can guarantee when the bit wide of forward and backward path metric is 8 bits that the Turbo code decoding performance does not have loss substantially.

A kind of Turbo code decoder state metric bit wide control method and device of being used for provided by the invention, result of calculation after each step computing in preceding, the reverse path metric calculation is controlled in the very limited scope, thereby make the computing figure place descend greatly, and this method for normalizing computing can be simplified the complexity of computing so that participating in all variablees of computing all is positive number.

Claims (2)

1. one kind is used for Turbo code decoder state metric bit wide control method, comprises:

Step 1: utilize Max-Log-MAP algorithm computation initial forward path metric and back calculation procedure to path metric;

${\widehat{\mathrm{\α}}}_k=\log \left[{\mathrm{\α}}_k\left(m\right)\right]==\underset{m^{\′}}{\max }(\frac{x_k{u}_k^i+y_k{v}_k^{{i,m}^{\′}}}{{\mathrm{\σ}}^2}F\left(z_k\right)+{\widehat{\mathrm{\α}}}_{k-1}\left(m^{\′}\right))---\left(6\right)$

Represent binary phase shift keying modulation or Quadrature Phase Shift Keying modulation respectively down, the information symbol sequence and the checking symbol sequence of the output of Turbo code encoder;

Step 2: side-play amount calculation procedure:

Step 2.1, comparator are according to F (z in formula (6) and (7) _k), obtain (z with respect to prior probability F _k) side-play amount z _Koffset:

z _koffset＝max(|z _k-max(0，z _k)|，|-max(0，z _k)|) (10)

The information bit x that step 2.2, comparator are imported according to the Turbo code decoder _kWith check bit y _kObtain side-play amount xy with respect to the decoder input signal _Koffset

xy _koffset＝2×max(|x _k/σ ²|，|y _k/σ ²|) (11)

Step 3: to path metric and offset addition, obtaining current forward path tolerance and back all is positive number to path metric with initial forward path tolerance and back;

$\begin{array}{c}{\widehat{\mathrm{\α}}}_k\left(m\right)=\log \left[{\mathrm{\α}}_k\left(m\right)\right]=\underset{m^{\′}}{\max }(\frac{x_k{u}_k^i+y_k{v}_k^{i,m^{\′}}}{{\mathrm{\σ}}^2}+F\left(z_k\right)+{\widehat{\mathrm{\α}}}_{k-1}\left(m^{\′}\right))+z_{\mathrm{offset}}+{\mathrm{xy}}_{\mathrm{offset}}---\left(12\right)\\ {\widehat{\mathrm{\β}}}_k\left(m\right)=\log \left[{\mathrm{\β}}_k\left(m\right)\right]=\underset{m^{\′}}{\max }(\frac{x_{k+1}{u}_{k+1}^i+y_{k+1}{v}_{k+1}^{{i,m}^{\′}}}{{\mathrm{\σ}}^2}+F\left(z_{k+1}\right)+{\widehat{\mathrm{\β}}}_{k+1}\left(m^{\′}\right))+z_{\mathrm{offset}}+{\mathrm{xy}}_{\mathrm{offset}}---\left(13\right)\end{array}$

Step 4: add up all current forward path tolerance α and current back minimum value: α to path metric β _MinAnd β _MinAnd

Step 5: utilize above-mentioned current forward path tolerance and current back minimum value to path metric,

Normalization is carried out to path metric in current forward path tolerance and back:

${\widehat{\mathrm{\α}}}_k\left(m\right)=\log \left[{\mathrm{\α}}_k\left(m\right)\right]$

$=\underset{m^{\′}}{\max }(\frac{x_k{u}_k^i+y_k{v}_k^{{i,m}^{\′}}}{{\mathrm{\σ}}^2}+F\left(z_k\right)+{\widehat{\mathrm{\α}}}_{k-1}\left(m^{\′}\right))+z_{\mathrm{offset}}+{\mathrm{xy}}_{\mathrm{offset}}-{\mathrm{\α}}_{\min }---\left(14\right)$

${\widehat{\mathrm{\β}}}_k\left(m\right)=\log \left[{\mathrm{\β}}_k\left(m\right)\right]$

$=\underset{m^{\′}}{\max }(\frac{x_{k+1}{u}_{k+1}^i+y_{k+1}{v}_{k+1}^{{i,m}^{\′}}}{{\mathrm{\σ}}^2}+F\left(z_{k+1}\right)+{\widehat{\mathrm{\β}}}_{k+1}\left(m^{\′}\right))+z_{\mathrm{offset}}+{\mathrm{xy}}_{\mathrm{offset}}-{\mathrm{\β}}_{\min }---\left(15\right)$

。

2. one kind is used for Turbo code decoder state measurement bit-width control device, it is characterized in that, comprises:

Utilize Max-Log-MAP algorithm computation initial forward path metric and back calculation element to path metric;

${\widehat{\mathrm{\α}}}_k=\log \left[{\mathrm{\α}}_k\left(m\right)\right]==\underset{m^{\′}}{\max }(\frac{x_k{u}_k^i+y_k{v}_k^{{i,m}^{\′}}}{{\mathrm{\σ}}^2}F\left(z_k\right)+{\widehat{\mathrm{\α}}}_{k-1}\left(m^{\′}\right))---\left(6\right)$

Represent binary phase shift keying modulation or Quadrature Phase Shift Keying modulation respectively down, the information symbol sequence and the checking symbol sequence of the output of Turbo code encoder;

Comparator is according to F (z in formula (6) and (7) _k), obtain (z with respect to prior probability F _k) side-play amount z _Koffset:

z _koffset＝max(|z _k-max(0，z _k)|，|-max(0，z _k)|) (10)

Comparator is according to the information bit x of Turbo code decoder input _kWith check bit y _kObtain side-play amount xy with respect to the decoder input signal _KoffsetThe side-play amount calculation element;

xy _koffset＝2×max(|x _k/σ ²|，|y _k/σ ²|) (11)

To path metric and offset addition, obtaining current forward path tolerance and back all is the adder of positive number to path metric with initial forward path tolerance and back;

${\widehat{\mathrm{\α}}}_k\left(m\right)=\log \left[{\mathrm{\α}}_k\left(m\right)\right]=\underset{m^{\′}}{\max }(\frac{x_k{u}_k^i+y_k{v}_k^{{i,m}^{\′}}}{{\mathrm{\σ}}^2}+F\left(z_k\right)+{\widehat{\mathrm{\α}}}_{k-1}\left(m^{\′}\right))+z_{\mathrm{offset}}+{\mathrm{xy}}_{\mathrm{offset}}---\left(12\right)$

${\widehat{\mathrm{\β}}}_k\left(m\right)=\log \left[{\mathrm{\β}}_k\left(m\right)\right]=\underset{m^{\′}}{\max }(\frac{x_{k+1}{u}_{k+1}^i+y_{k+1}{v}_{k+1}^{{i,m}^{\′}}}{{\mathrm{\σ}}^2}+F\left(z_{k+1}\right)+{\widehat{\mathrm{\β}}}_{k+1}\left(m^{\′}\right))+z_{\mathrm{offset}}+{\mathrm{xy}}_{\mathrm{offset}}---\left(13\right)$

Add up all current forward path tolerance α and current back minimum value: α to path metric β _MinAnd β _MinMinimum value selector; And

Utilize above-mentioned current forward path tolerance and current back minimum value, normalized subtracter is carried out to path metric in current forward path tolerance and back to path metric

${\widehat{\mathrm{\α}}}_k\left(m\right)=\log \left[{\mathrm{\α}}_k\left(m\right)\right]$

$=\underset{m^{\′}}{\max }(\frac{x_k{u}_k^i+y_k{v}_k^{{i,m}^{\′}}}{{\mathrm{\σ}}^2}+F\left(z_k\right)+{\widehat{\mathrm{\α}}}_{k-1}\left(m^{\′}\right))+z_{\mathrm{offset}}+{\mathrm{xy}}_{\mathrm{offset}}-{\mathrm{\α}}_{\min }---\left(14\right)$

${\widehat{\mathrm{\β}}}_k\left(m\right)=\log \left[{\mathrm{\β}}_k\left(m\right)\right]$

$=\underset{m^{\′}}{\max }(\frac{x_{k+1}{u}_{k+1}^i+y_{k+1}{v}_{k+1}^{{i,m}^{\′}}}{{\mathrm{\σ}}^2}+F\left(z_{k+1}\right)+{\widehat{\mathrm{\β}}}_{k+1}\left(m^{\′}\right))+z_{\mathrm{offset}}+{\mathrm{xy}}_{\mathrm{offset}}-{\mathrm{\β}}_{\min }---\left(15\right).$

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