CN107919877A - Interpretation method and device based on SOVA decoder algorithm SOVA - Google Patents

Interpretation method and device based on SOVA decoder algorithm SOVA Download PDF

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CN107919877A
CN107919877A CN201610878471.1A CN201610878471A CN107919877A CN 107919877 A CN107919877 A CN 107919877A CN 201610878471 A CN201610878471 A CN 201610878471A CN 107919877 A CN107919877 A CN 107919877A
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metric difference
value
sampled point
state node
group
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CN107919877B (en
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裴睿淋
黄勤
王加庆
孙韶辉
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China Academy of Telecommunications Technology CATT
Datang Mobile Communications Equipment Co Ltd
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China Academy of Telecommunications Technology CATT
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    • H—ELECTRICITY
    • H03—ELECTRONIC CIRCUITRY
    • H03M—CODING; DECODING; CODE CONVERSION IN GENERAL
    • H03M13/00—Coding, decoding or code conversion, for error detection or error correction; Coding theory basic assumptions; Coding bounds; Error probability evaluation methods; Channel models; Simulation or testing of codes
    • H03M13/37—Decoding methods or techniques, not specific to the particular type of coding provided for in groups H03M13/03 - H03M13/35
    • H03M13/39—Sequence estimation, i.e. using statistical methods for the reconstruction of the original codes
    • H03M13/41—Sequence estimation, i.e. using statistical methods for the reconstruction of the original codes using the Viterbi algorithm or Viterbi processors
    • H03M13/4138—Sequence estimation, i.e. using statistical methods for the reconstruction of the original codes using the Viterbi algorithm or Viterbi processors soft-output Viterbi algorithm based decoding, i.e. Viterbi decoding with weighted decisions
    • H03M13/4146—Sequence estimation, i.e. using statistical methods for the reconstruction of the original codes using the Viterbi algorithm or Viterbi processors soft-output Viterbi algorithm based decoding, i.e. Viterbi decoding with weighted decisions soft-output Viterbi decoding according to Battail and Hagenauer in which the soft-output is determined using path metric differences along the maximum-likelihood path, i.e. "SOVA" decoding
    • H—ELECTRICITY
    • H03—ELECTRONIC CIRCUITRY
    • H03M—CODING; DECODING; CODE CONVERSION IN GENERAL
    • H03M13/00—Coding, decoding or code conversion, for error detection or error correction; Coding theory basic assumptions; Coding bounds; Error probability evaluation methods; Channel models; Simulation or testing of codes
    • H03M13/37—Decoding methods or techniques, not specific to the particular type of coding provided for in groups H03M13/03 - H03M13/35
    • H03M13/39—Sequence estimation, i.e. using statistical methods for the reconstruction of the original codes
    • H03M13/41—Sequence estimation, i.e. using statistical methods for the reconstruction of the original codes using the Viterbi algorithm or Viterbi processors

Abstract

The invention discloses a kind of interpretation method and device based on SOVA, solves the increase of the length with the corresponding information bit of receiving sequence, the complexity of SOVA is also the increase the problem of.Method includes：Using viterbi algorithm, in the grid chart of setting, determine the corresponding maximum likelihood path of receiving sequence, and calculate the metric difference of the contended path of each state node and the maximum likelihood path in the maximum likelihood path, the grid chart is used for the state change for characterizing encoder at different moments；According to the value of the metric difference, from the state node in the maximum likelihood path, K state node is selected to be determined as sampled point, K is positive integer；Using the sampled point as backtracking node, backtracking process is carried out, to update the log-likelihood ratio LLR value for each information bit that the receiving sequence includes.So as on the premise of it ensure that system performance, reduce decoding complexity, improve decoding speed, it is easier to hardware realization.

Description

Interpretation method and device based on SOVA decoder algorithm SOVA
Technical field
It is more particularly to a kind of to be based on SOVA decoder algorithm (Soft the present invention relates to field of communication technology Output Viterbi Algorithm, abbreviation SOVA) interpretation method and device.
Background technology
Turbo code is a kind of channel coding technology of forward error correction, at present Long Term Evolution (Long Term Evolution, Abbreviation LTE) data traffic channels are encoded using Turbo code in system.Due to traditional max log posterior probability (max- Log-map) decoding algorithm implementation complexity is higher, and power consumption efficiency is not high, and degree of parallelism is low, therefore max-log-map decoding algorithms The inapplicable scene for requiring to realize high-throughput.It is at least as 3GPP defines newly the eat dishes without rice or wine handling capacities of downlink (DL) of 5G 20Gbps, therefore in order to reduce power consumption, realize the high-throughput index of 5G requirements, it is desirable to using the quick Turbo of low complex degree Code decoding algorithm.
SOVA decoder algorithm (SOVA) is a kind of based on viterbi algorithm (Viterbi Algorithm, abbreviation VA decoding algorithm), SOVA define bit error probability on the basis of viterbi algorithm, using the cumulative metric difference in path With path error probability, and these mistakes are converted into log-likelihood ratio (Log-Likelihood Ratio, abbreviation LLR), made Exported to be soft into row decoding.Since SOVA complexities are relatively low, it is easy to accomplish, it is widely used in convolutional code, Turbo code decoding.Adopt The process handled with SOVA into row decoding is as follows：
The first step, using viterbi algorithm, determine the corresponding maximum likelihood of receiving sequence (Maximum Likelihood, Abbreviation ML) path.Wherein, by grid (trellis) figure of encoding state, the path with maximum metric is found, this road Footpath is known as maximum likelihood path, and VA algorithms can be described as follows：
step 1：In initial time t=m, the path metric of each state node is calculated, records above-mentioned measurement and corresponding Path；
step 2：T=t+1 is made, calculated the path metric for all branches for entering each state node and a upper moment The path metric summed of path metric, choose the path with maximum path measurement and be determined as survivor path；
step 3：If t<H+m, returns to step 2, wherein, h is coding information length；Otherwise, last moment pair The survivor path answered is maximum likelihood path.
Second step, recalls all labeled contended paths, updates the LLR value of receiving sequence.
Specifically, path error probability and bit error probability are introduced, after finding ML paths by viterbi algorithm, Each state is recalled again, updates corresponding bit error rate, LLR value is obtained by bit error rate.Assuming that m (s, t) To terminate at the path metric in the ML paths of state s in t moment, cm (s, t) is the contended path that state s is terminated in t moment Path metric, mdiff (s, t)=m (s, t)-cm (s, t) is path metric difference.Assuming that during ML paths are solved, often The mdiff (s, t) of each state at a moment is calculated, then trace-back process is expressed as follows：
(1) LLR value for initializing each state node on survivor path is+∞；
(2) recall forward since the state node of last moment t=L, untill initial state node；
(3) each information bit in the contended path and survivor path of the state node is compared, if on two paths Bit value it is identical, then do not update the LLR value corresponding to corresponding bit, if it is not the same, then with the LLR value of the bit with Minimum value in mdiff (s, t) updates the LLR value of the bit；
(4) t=t-1, continues to recall, until start node；
(5) symbol of LLR is adjusted with the bit symbol of hard decision.
The complexity of SOVA is mainly determined that the computation complexity of trace-back process is O (δ SL), and wherein δ is by its back tracking operation Traceback length, S are the number of state node, and L is the length of the corresponding information bit of receiving sequence.Under normal circumstances, SOVA exists When realizing, only the state node on ML paths is recalled, therefore the computation complexity of trace-back process can shorten to O (δ L).As it can be seen that the increase of the length with the corresponding information bit of receiving sequence, the complexity of SOVA is also increasing.
The content of the invention
An embodiment of the present invention provides a kind of interpretation method and device for being based on SOVA decoder algorithm (SOVA), Solves the increase of the length with the corresponding information bit of receiving sequence, the complexity of SOVA is also the increase the problem of.
First aspect, there is provided a kind of interpretation method based on SOVA, the described method includes：
Using viterbi algorithm, in the grid chart of setting, the corresponding maximum likelihood path of receiving sequence is determined, and calculate The metric difference of the contended path of each state node and the maximum likelihood path, the grid chart in the maximum likelihood path For characterizing the state change of encoder at different moments；
According to the value of the metric difference, from the state node in the maximum likelihood path, select K state node true It is set to sampled point, K is positive integer；
Using the sampled point as backtracking node, backtracking process is carried out, to update each letter that the receiving sequence includes Cease the log-likelihood ratio LLR value of bit.
In a kind of possible embodiment,The L is the length of the corresponding information bit of the receiving sequence Degree, the M are the downsampling factor of setting,Expression rounds up computing.
In a kind of possible embodiment, according to the value of the metric difference, from the state section in the maximum likelihood path In point, K state node is selected to be determined as sampled point, including：
The metric difference is ranked up according to order from small to large, selected and sorted position is located at the metric difference of preceding K Corresponding state node is determined as sampled point；Or
The metric difference is divided into P groups, according to the value of every group of metric difference, at least one degree is selected from every group of metric difference The poor corresponding states node of amount is determined as sampled point, and the P is positive integer.
In a kind of possible embodiment, the metric difference is divided into P groups, including：
According to the numbering of the metric difference, the metric difference is divided into P groups, the numbering of every group of metric difference included successively Continuously；Or
According to the numbering of the metric difference, the metric difference numbered at intervals of P is divided into one group successively.
In a kind of possible embodiment, the value of the P is K；Or
The value of the P isThe L is the length of the corresponding information bit of the receiving sequence, and n is just whole Number, M are the downsampling factor of setting,Expression rounds up computing.
In a kind of possible embodiment, according to the value of every group of metric difference, at least one degree is selected from every group of metric difference The poor corresponding states node of amount is determined as sampled point, including：
If the value of the P is K, according to the value of the metric difference, from every group of metric difference, the metric difference pair of minimum is selected State node is answered to be determined as sampled point；Or
If the value of the P isFrom every group of metric difference, selected metric difference is arranged according to order from small to large The corresponding state node of metric difference of n is determined as sampled point before being listed in.
Second aspect, there is provided a kind of computer-readable recording medium, wherein executable program code is stored with, the journey Sequence code is realizing the method described in first aspect.
The third aspect, there is provided a kind of code translator based on SOVA, described device include：
Path determination module, for using viterbi algorithm, in the grid chart of setting, determining that receiving sequence is corresponding most Maximum-likelihood path, and calculate the contended path of each state node and the maximum likelihood path in the maximum likelihood path Metric difference, the grid chart are used for the state change for characterizing encoder at different moments；
Sampling module, for the value according to the metric difference, from the state node in the maximum likelihood path, selection K state node is determined as sampled point, and K is positive integer；
Backtracking module, for using the sampled point as backtracking node, backtracking process being carried out, to update the receiving sequence Comprising each information bit log-likelihood ratio LLR value.
In a kind of possible embodiment,The L is the length of the corresponding information bit of the receiving sequence Degree, the M are the downsampling factor of setting,Expression rounds up computing.
In a kind of possible embodiment, the sampling module is specifically used for：
The metric difference is ranked up according to order from small to large, selected and sorted position is located at the metric difference of preceding K Corresponding state node is determined as sampled point；Or
The metric difference is divided into P groups, according to the value of every group of metric difference, at least one degree is selected from every group of metric difference The poor corresponding states node of amount is determined as sampled point, and the P is positive integer.
In a kind of possible embodiment, the sampling module is specifically used for：
According to the numbering of the metric difference, the metric difference is divided into P groups, the numbering of every group of metric difference included successively Continuously；Or
According to the numbering of the metric difference, the metric difference numbered at intervals of P is divided into one group successively.
In a kind of possible embodiment, the value of the P is K；Or
The value of the P isThe L is the length of the corresponding information bit of the receiving sequence, and n is just whole Number, M are the downsampling factor of setting,Expression rounds up computing.
In a kind of possible embodiment, the sampling module is specifically used for：
If the value of the P is K, according to the value of the metric difference, from every group of metric difference, the metric difference pair of minimum is selected State node is answered to be determined as sampled point；Or
If the value of the P isFrom every group of metric difference, selected metric difference is arranged according to order from small to large The corresponding state node of metric difference of n is determined as sampled point before being listed in.
Fourth aspect, there is provided a kind of code translator based on SOVA, including transceiver and be connected with the transceiver At least one processor, wherein：
The processor, for reading the program in memory, performs following process：
Using viterbi algorithm, in the grid chart of setting, the corresponding maximum likelihood path of receiving sequence is determined, and calculate The metric difference of the contended path of each state node and the maximum likelihood path, the grid chart in the maximum likelihood path For characterizing the state change of encoder at different moments；
According to the value of the metric difference, from the state node in the maximum likelihood path, select K state node true It is set to sampled point, K is positive integer；And
Using the sampled point as backtracking node, backtracking process is carried out, to update each letter that the receiving sequence includes Cease the log-likelihood ratio LLR value of bit；
The transceiver, for data to be received and sent under the control of the processor.
In a kind of possible embodiment,The L is the length of the corresponding information bit of the receiving sequence Degree, the M are the downsampling factor of setting,Expression rounds up computing.
In a kind of possible embodiment, the processor reads the program in the memory, specifically performs following mistake Journey：
The metric difference is ranked up according to order from small to large, selected and sorted position is located at the metric difference of preceding K Corresponding state node is determined as sampled point；Or
The metric difference is divided into P groups, according to the value of every group of metric difference, at least one degree is selected from every group of metric difference The poor corresponding states node of amount is determined as sampled point, and the P is positive integer.
In a kind of possible embodiment, the processor reads the program in the memory, specifically performs following mistake Journey：
According to the numbering of the metric difference, the metric difference is divided into P groups, the numbering of every group of metric difference included successively Continuously；Or
According to the numbering of the metric difference, the metric difference numbered at intervals of P is divided into one group successively.
In a kind of possible embodiment, the value of the P is K；Or
The value of the P isThe L is the length of the corresponding information bit of the receiving sequence, and n is just whole Number, M are the downsampling factor of setting,Expression rounds up computing.
In a kind of possible embodiment, the processor reads the program in the memory, specifically performs following mistake Journey：
If the value of the P is K, according to the value of the metric difference, from every group of metric difference, the metric difference pair of minimum is selected State node is answered to be determined as sampled point；Or
If the value of the P isFrom every group of metric difference, selected metric difference is arranged according to order from small to large The corresponding state node of metric difference of n is determined as sampled point before being listed in.
In method and apparatus provided in an embodiment of the present invention, using viterbi algorithm, in the grid chart of setting, determine to connect Receive the corresponding maximum likelihood path of sequence, and calculate in the maximum likelihood path contended path of each state node with it is described The metric difference of maximum likelihood path, according to the value of the metric difference, from the state node in the maximum likelihood path, selection K state node is determined as sampled point；Using the sampled point as backtracking node, backtracking process is carried out, to update the reception The LLR value for each information bit that sequence includes.So that on the premise of it ensure that system performance, only to identified sampled point Backtracking process is carried out, the LLR value for each information bit that the receiving sequence includes is determined, reduces decoding complexity, is improved Decoding speed, realizes quick, efficient decoding processing, it is easier to hardware realization.
Brief description of the drawings
Fig. 1 is the schematic diagram of the grid chart in the embodiment of the present invention；
Fig. 2 is a kind of schematic diagram of the interpretation method based on SOVA provided in an embodiment of the present invention；
Fig. 3 is a kind of schematic diagram of the code translator based on SOVA provided in an embodiment of the present invention；
Fig. 4 is the schematic diagram of another code translator based on SOVA provided in an embodiment of the present invention.
Embodiment
To make the purpose, technical scheme and advantage of the embodiment of the present invention clearer, below in conjunction with the embodiment of the present invention In attached drawing, the technical solution in the embodiment of the present invention is clearly and completely described, it is clear that described embodiment is Part of the embodiment of the present invention, instead of all the embodiments.Based on the embodiments of the present invention, those of ordinary skill in the art All other embodiments obtained without creative efforts, belong to the scope of protection of the invention.
Scheme described in the embodiment of the present invention can be used for various communication systems, for example, 2G, 3G, 4G, 5G communication system and Next generation communication system, such as global system for mobile communications (Global System for Mobile communications, Abbreviation GSM), CDMA (Code Division Multiple Access, abbreviation CDMA) system, time division multiple acess (Time Division Multiple Access, abbreviation TDMA) system, wideband code division multiple access (Wideband Code Division Multiple Access Wireless, abbreviation WCDMA), frequency division multiple access (Frequency Division Multiple Addressing, abbreviation FDMA) system, Orthogonal Frequency Division Multiple Access (Orthogonal Frequency-Division Multiple Access, abbreviation OFDMA) system, Single Carrier Frequency Division Multiple Access (SC-FDMA) system, General Packet Radio Service (General Packet Radio Service, abbreviation GPRS) system, Long Term Evolution (Long Term Evolution, abbreviation LTE) system etc..
Grid chart in the embodiment of the present invention, is the signal that the state transfer of encoder is unfolded sequentially in time Figure, Fig. 1 are a kind of schematic diagram of grid chart, are 5 Fig. 1 shows information bit length, and register number m is the net of 2 convolutional code Trrellis diagram.Encoder shares 2m=4 states, i.e. S in Fig. 10~S3Shown state node, any two state node in Fig. 1 Between side on mark numerical value such as 111, the presentation code device such as 010 output code word.The process of decoding is sought in this net A path is found in trrellis diagram so that the output in this path and actual receiving sequence are closest, this path is denoted as maximum Likelihood path, i.e. ML paths.Viterbi algorithm can be used for search ML paths.
As can be seen that removing at m time (i.e. moment 0 and the moment that time t is starting from the grid chart shown in Fig. 1 1), and outside the m moment (i.e. 6 and 7 moment of moment) of ending, in moment 2-5, each state node has 2 sides to enter The state node is left on the state node, 2 sides, corresponded to respectively input for 0 and input be 1 when state transfer.It is i.e. each State has that two paths are reachable, and when decoding needs to contrast the measurement of this two paths, retains the path with larger measurement, this Path is known as survivor path, gives up the path of smaller measurement, this path is known as contended path.Wherein, measurement is used to characterize and appoints The length in the path between two nodes of meaning, for example, the measurement in path can be Hamming distance etc..The embodiment of the present invention is not satisfied the need The concrete form of the measurement in footpath is defined.
For SOVA, ML paths are determined by viterbi algorithm first, it is assumed that ML paths are the path shown in thick line. Next, SOVA needs to recall the state node on ML paths, to determine to need the soft information value exported, it is therefore desirable to L state node on ML paths is recalled.At each state node in ML paths, there are 2 sides to enter the state Node, such as at the time of t=3, state node S2, this state may be by state node S3Reach, it is also possible to by state section Point S1Reach, calculate path S respectively3→S2Measurement and path S1→S2Measurement, if path S3→S2Measurement be more than path S1 →S2Measurement, then surviving path S3→S2, path S3→S2Referred to as survivor path, gives up path S1→S2, path S1→S2Claim Be contended path.
Contrast is only needed to preserve survivor path and its metric in traditional SOVA algorithms, and in order to protect in the embodiment of the present invention System performance is demonstrate,proved, the contended path of all state nodes and the metric difference in ML paths on ML paths is calculated, is denoted as △1~△L, its In, the numbering of the metric difference calculated is sequentially arranged, and the quantity of metric difference is the corresponding information ratio of receiving sequence Special length.In order to reduce decoding complexity in the embodiment of the present invention, based on △1~△LK state node of selection is determined as adopting Sampling point, and backtracking process only is carried out to sampled point, so that it is determined that the LLR value for each information bit that the receiving sequence includes.
The embodiment of the present invention is described in further detail with reference to Figure of description.It is it should be appreciated that described herein Embodiment be merely to illustrate and explain the present invention, be not intended to limit the present invention.
In embodiment illustrated in fig. 2, there is provided a kind of interpretation method based on SOVA, the described method includes：
S21, using viterbi algorithm, in the grid chart of setting, determine the corresponding maximum likelihood path of receiving sequence, and Calculate the metric difference of the contended path of each state node and the maximum likelihood path in the maximum likelihood path, the net Trrellis diagram is used for the state change for characterizing encoder at different moments；
S22, the value according to the metric difference, from the state node in the maximum likelihood path, select K state section Point is determined as sampled point, and K is positive integer；
S23, using the sampled point as backtracking node, carry out backtracking process, with update the receiving sequence include it is every The LLR value of a information bit.
In the embodiment of the present invention, using viterbi algorithm, in the grid chart of setting, the corresponding maximum of receiving sequence is determined Likelihood path, and calculate the degree of the contended path of each state node and the maximum likelihood path in the maximum likelihood path Amount is poor, according to the value of the metric difference, from the state node in the maximum likelihood path, selects K state node to determine For sampled point；Using the sampled point as backtracking node, backtracking process is carried out, to update each letter that the receiving sequence includes Cease the LLR value of bit.So as on the premise of it ensure that system performance, only carry out backtracking process to identified sampled point, really The LLR value for each information bit that the fixed receiving sequence includes, reduces decoding complexity, improves decoding speed, realizes Quick, efficient decoding processing, it is easier to hardware realization.
In a kind of possible embodiment,The L is the length of the corresponding information bit of the receiving sequence Degree, the M are the downsampling factor of setting,Expression rounds up computing.
Based on any of the above-described embodiment, since metric difference is smaller, the calculating for the LLR value answered receiving sequence pair influences to get over Greatly, therefore the corresponding state node of the less metric difference of selection is as sampled point.Correspondingly, according to the metric difference in S22 Value, from the state node in the maximum likelihood path, selects K state node to be determined as sampled point, including following two Possible embodiment：
Mode 1, directly sequence sampling, will the metric difference be ranked up according to order from small to large, selected and sorted The corresponding state node of metric difference that position is located at preceding K is determined as sampled point.
Specifically, directly to Δ1,Δ2,...,ΔLIt is ranked up according to order from small to large, is selected after sequence The minimum corresponding state node of K metric difference is as sampled point.
It is minimum value in the overall situation which, which directly sorts and samples the metric difference of selection, it is ensured that the performance of decoding algorithm, But need to be ranked up L data in hardware realization, choose K minimum value, it is necessary to expend certain hardware resource.
Mode 2, block sampling, will the metric difference be divided into P groups, according to the value of every group of metric difference, from every group of measurement At least one metric difference corresponding states node is selected to be determined as sampled point in difference, the P is positive integer.
Which further includes following two possible implementations again：
Mode 21, contiguous segmentation sampling, i.e., according to the numbering of the metric difference, be divided into P groups by the metric difference successively, The numbering of every group of metric difference included is continuous.
Optionally, the value of the P is K；Or the value of the P isThe L is the receiving sequence pair The length for the information bit answered, n are positive integer, and M is the downsampling factor of setting,Expression rounds up computing.
If specifically, the value of the P is K, by Δ1,Δ2,...,ΔLIt is divided into continuous K sections of progress partial ordering, I.e. from Δ1Start, oftenA metric difference is divided into one group, amounts to K groups, selects the corresponding state of metric difference minimum in every group Node is sampled point；
If the value of the P is(being denoted as N=n*M, i.e. N is the integral multiple of downsampling factor), then by Δ1, Δ2,...,ΔLIt is divided into continuousDuan Jinhang partial orderings, i.e., from Δ1Start, △1-△NFor 1 group, △N+1-△N*2For 1 group ... amounts toGroup.
In which, according to the value of every group of metric difference in S22, at least one metric difference is selected to correspond to from every group of metric difference State node is determined as sampled point, further comprises：
If the value of the P is K, according to the value of the metric difference, from every group of metric difference, the metric difference pair of minimum is selected State node is answered to be determined as sampled point；Or
If the value of the P isFrom every group of metric difference, selected metric difference is arranged according to order from small to large The corresponding state node of metric difference of n is determined as sampled point before being listed in.
Which selects the minimum value in each metric difference group by way of contiguous segmentation, realizes quick.
Mode 22, space segmentation sampling, i.e., according to the numbering of the metric difference, will number the metric difference at intervals of P successively It is divided into one group.
Optionally, the value of the P is K；Or the value of the P isThe L is the receiving sequence pair The length for the information bit answered, n are positive integer, and M is the downsampling factor of setting,Expression rounds up computing.
If specifically, the value of the P is K, the numbering of the metric difference and K are subjected to complementation, remainder is transported The metric difference that the result of calculation is identical is divided into one group, obtains K group metric differences, such as △1, △K+1, △2*K+1... it is 1 group, △2, △K+2, △2*K+2... it is 1 group, and so on；
The value of the P is(being denoted as N=n*M, i.e. N is the integral multiple of downsampling factor), then by the metric difference Numbering withComplementation is carried out, the identical metric difference of the result of complementation is divided into one group, is obtainedGroup metric difference.
In which, according to the value of every group of metric difference in S22, at least one metric difference is selected to correspond to from every group of metric difference State node is determined as sampled point, further comprises：
If the value of the P is K, according to the value of the metric difference, from every group of metric difference, the metric difference pair of minimum is selected State node is answered to be determined as sampled point；Or
If the value of the P isFrom every group of metric difference, selected metric difference is arranged according to order from small to large The corresponding state node of metric difference of n is determined as sampled point before being listed in.
Which will be divided into one section by space segmentation sampling algorithm at intervals of the data of P, in each data segment, selection Minimum metric difference is sampled, and so not only reduces hardware resource consumption, but also reduces the correlation between sampled data, can be with The down-sampled of metric difference is quickly realized under conditions of performance is ensured.
Based on any of the above-described embodiment, using the sampled point as backtracking node in S23, backtracking process is carried out, with renewal The LLR value for each information bit that the receiving sequence includes, it is specific as follows：
1) it is+∞ to initialize each corresponding LLR value of state node in maximum likelihood path；
2) recall forward since the state node of last moment t=L, untill initial state node, to every A state node performs following processing：
Compare each bit in the contended path and maximum likelihood path of the state node；
If the value of two bits is identical, the LLR value corresponding to corresponding bit is not updated；
If the value of two bits differs, the LLR value of the bit is updated with minimum value；
3) symbol of LLR is adjusted with the bit symbol of hard decision, so as to fulfill complete outputs of the SOVA to LLR.
It is L that traditional SOVA algorithms, which need the number of the state node of backtracking process, and the drop of S22 is passed through in the embodiment of the present invention , it is necessary to which the state node number of backtracking process is K after sampling, so as to reduce processing complexity.But stilled need in decoding The LLR value of L state node is exported, it is therefore desirable to the LLR value of remaining L-K node is estimated, specifically such as Under：
Since the path metric difference of partial status node in maximum likelihood path after sampling is omitted, it is impossible to update its correspondence Information bit LLR value, it is therefore desirable to the LLR value of the state node to being omitted estimates, estimate includes channel External information two parts of interior information and neighbouring not ignored LLR, its calculation formula are：LLR (l)=| LLRi(l)|+|LLRn (l)|；
Wherein LLRn(l) it is the LLR, LLR of sampled point nearest distance li(l) it is the interior information of carrying out self-channel, it specifically may be used Calculated by following formula：
|LLRi(l)|≈|0.5Lc*(rl*cl(ul=+1)-rl*cl(ul=-1)) |+| La (l) |；
Wherein, rlRepresent the receiving sequence at l moment, ulRepresent the information bit at l moment, clRepresent corresponding code word, cl(ul =+1) code word when input information is 1, c are representedl(ul=-1) code word when input information is 0 is represented,Represent Channel confidence factor,Represent the prior information of information bit.
Method provided in an embodiment of the present invention can also be applied to the network equipment with application terminal equipment.
Wherein, terminal device is also referred to as user equipment (User Equipment, referred to as " UE "), mobile station (Mobile Station, referred to as " MS "), mobile terminal (Mobile Terminal) etc., optionally, which can possess The ability to communicate through wireless access network (Radio Access Network, RAN) with one or more core nets, for example, Terminal can be mobile phone (or being " honeycomb " phone) or computer with mobile property etc., for example, terminal can be with It is portable, pocket, hand-held, built-in computer or vehicle-mounted mobile device.
The network equipment can be base station (for example, access point), refer to the accession in net and pass through one or more on interface in the air Sector and the equipment of wireless terminal communications.Base station can be used for mutually being changed received air frame and IP packets, as nothing Router between the remainder of line terminal and access net, wherein the remainder for accessing net may include Internet protocol (IP) net Network.Attribute management of the base station also tunable to air interface.For example, base station can be base station (BTS, Base in GSM or CDMA Transceiver Station) or WCDMA in base station (NodeB), can also be the evolved base station in LTE (NodeB or eNB or e-NodeB, evolutional Node B), does not limit in present aspect embodiment.
Above method process flow can realize that the software program can be stored in storage medium with software program, when When the software program of storage is called, above method step is performed.
Based on same inventive concept, a kind of code translator based on SOVA is additionally provided in the embodiment of the present invention, due to this A kind of interpretation method based on SOVA of the principle that device solves the problems, such as shown in above-mentioned Fig. 2 is similar, therefore the implementation of the device The implementation of method is may refer to, overlaps will not be repeated.
In embodiment illustrated in fig. 3, there is provided a kind of code translator based on SOVA, described device include：
Path determination module 31, for using viterbi algorithm, in the grid chart of setting, determining that receiving sequence is corresponding Maximum likelihood path, and calculate the contended path of each state node and the maximum likelihood path in the maximum likelihood path Metric difference, the grid chart is used for the state change for characterizing encoder at different moments；
Sampling module 32, for the value according to the metric difference, from the state node in the maximum likelihood path, choosing Select K state node and be determined as sampled point, K is positive integer；
Backtracking module 33, for using the sampled point as backtracking node, backtracking process being carried out, to update the Receiving Order Arrange the log-likelihood ratio LLR value of each information bit included.
Optionally,The L is the length of the corresponding information bit of the receiving sequence, and the M is setting Downsampling factor,Expression rounds up computing.
In a kind of possible embodiment, the sampling module 32 is specifically used for：
The metric difference is ranked up according to order from small to large, selected and sorted position is located at the metric difference of preceding K Corresponding state node is determined as sampled point；Or
The metric difference is divided into P groups, according to the value of every group of metric difference, at least one degree is selected from every group of metric difference The poor corresponding states node of amount is determined as sampled point, and the P is positive integer.
Further, the sampling module 32 is specifically used for：
According to the numbering of the metric difference, the metric difference is divided into P groups, the numbering of every group of metric difference included successively Continuously；Or
According to the numbering of the metric difference, the metric difference numbered at intervals of P is divided into one group successively.
Optionally, the value of the P is K；Or
The value of the P isThe L is the length of the corresponding information bit of the receiving sequence, and n is just whole Number, M are the downsampling factor of setting,Expression rounds up computing.
In a kind of possible embodiment, the sampling module 32 is specifically used for：
If the value of the P is K, according to the value of the metric difference, from every group of metric difference, the metric difference pair of minimum is selected State node is answered to be determined as sampled point；Or
If the value of the P isFrom every group of metric difference, selected metric difference is arranged according to order from small to large The corresponding state node of metric difference of n is determined as sampled point before being listed in.
In embodiment illustrated in fig. 4, there is provided a kind of code translator based on SOVA, including transceiver and with the transmitting-receiving At least one processor of machine connection, wherein：
Processor 500, for reading the program in memory 520, performs following process：
Using viterbi algorithm, in the grid chart of setting, the corresponding maximum likelihood path of receiving sequence is determined, and calculate The metric difference of the contended path of each state node and the maximum likelihood path, the grid chart in the maximum likelihood path For characterizing the state change of encoder at different moments；
According to the value of the metric difference, from the state node in the maximum likelihood path, select K state node true It is set to sampled point, K is positive integer；And
Using the sampled point as backtracking node, backtracking process is carried out, to update each letter that the receiving sequence includes Cease the log-likelihood ratio LLR value of bit；
Transceiver 510, for receiving and sending data under control of the processor 500.
Wherein, in Fig. 4, bus architecture can include the bus and bridge of any number of interconnection, specifically by processor 500 The various circuits for the memory that the one or more processors and memory 520 of representative represent link together.Bus architecture is also Various other circuits of such as ancillary equipment, voltage-stablizer and management circuit or the like can be linked together, these are all It is it is known in the art, therefore, no longer it is described further herein.Bus interface provides interface.Transceiver 510 can To be multiple element, i.e., including transmitter and transceiver, there is provided for the list to communicate over a transmission medium with various other devices Member.Processor 500 is responsible for bus architecture and common processing, can also provide various functions, including timing, periphery connects Mouthful, voltage adjusting, power management and other control functions.Memory 520 can store processor 500 and perform operation when institute The data used.
Optionally, processor 500 can be that centre buries device (CPU), application-specific integrated circuit (Application Specific Integrated Circuit, abbreviation ASIC), field programmable gate array (Field-Programmable Gate Array, abbreviation FPGA) or Complex Programmable Logic Devices (Complex Programmable Logic Device, letter Claim CPLD).
Optionally,The L is the length of the corresponding information bit of the receiving sequence, and the M is setting Downsampling factor,Expression rounds up computing.
In a kind of possible embodiment, processor 500 reads the program in memory 520, specifically performs following process：
The metric difference is ranked up according to order from small to large, selected and sorted position is located at the metric difference of preceding K Corresponding state node is determined as sampled point；Or
The metric difference is divided into P groups, according to the value of every group of metric difference, at least one degree is selected from every group of metric difference The poor corresponding states node of amount is determined as sampled point, and the P is positive integer.
Further, processor 500 reads the program in memory 520, specifically performs following process：
According to the numbering of the metric difference, the metric difference is divided into P groups, the numbering of every group of metric difference included successively Continuously；Or
According to the numbering of the metric difference, the metric difference numbered at intervals of P is divided into one group successively.
Optionally, the value of the P is K；Or
The value of the P isThe L is the length of the corresponding information bit of the receiving sequence, and n is just whole Number, M are the downsampling factor of setting,Expression rounds up computing.
In a kind of possible embodiment, processor 500 reads the program in memory 520, specifically performs following process：
If the value of the P is K, according to the value of the metric difference, from every group of metric difference, the metric difference pair of minimum is selected State node is answered to be determined as sampled point；Or
If the value of the P isFrom every group of metric difference, selected metric difference is arranged according to order from small to large The corresponding state node of metric difference of n is determined as sampled point before being listed in.
In device provided in an embodiment of the present invention, using viterbi algorithm, in the grid chart of setting, receiving sequence is determined Corresponding maximum likelihood path, and calculate in the maximum likelihood path contended path of each state node with it is described it is maximum seemingly The metric difference in right path, according to the value of the metric difference, from the state node in the maximum likelihood path, selects K shape State node is determined as sampled point；Using the sampled point as backtracking node, backtracking process is carried out, to update the receiving sequence bag The LLR value of each information bit contained.So as on the premise of it ensure that system performance, only be returned to identified sampled point Trace back processing, determine the LLR value for each information bit that the receiving sequence includes, reduce decoding complexity, improve decoding Speed, realizes quick, efficient decoding processing, it is easier to hardware realization.
It should be understood by those skilled in the art that, the embodiment of the present invention can be provided as method, system or computer program Product.Therefore, the present invention can use the reality in terms of complete hardware embodiment, complete software embodiment or combination software and hardware Apply the form of example.Moreover, the present invention can use the computer for wherein including computer usable program code in one or more The computer program production that usable storage medium is implemented on (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.) The form of product.
The present invention be with reference to according to the method for the embodiment of the present invention, the flow of equipment (system) and computer program product Figure and/or block diagram describe.It should be understood that it can be realized by computer program instructions every first-class in flowchart and/or the block diagram The combination of flow and/or square frame in journey and/or square frame and flowchart and/or the block diagram.These computer programs can be provided The processors of all-purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices is instructed to produce A raw machine so that the instruction performed by computer or the processor of other programmable data processing devices, which produces, to be used in fact The device for the function of being specified in present one flow of flow chart or one square frame of multiple flows and/or block diagram or multiple square frames.
These computer program instructions, which may also be stored in, can guide computer or other programmable data processing devices with spy Determine in the computer-readable memory that mode works so that the instruction being stored in the computer-readable memory, which produces, to be included referring to Make the manufacture of device, the command device realize in one flow of flow chart or multiple flows and/or one square frame of block diagram or The function of being specified in multiple square frames.
These computer program instructions can be also loaded into computer or other programmable data processing devices so that counted Series of operation steps is performed on calculation machine or other programmable devices to produce computer implemented processing, thus in computer or The instruction performed on other programmable devices is provided and is used for realization in one flow of flow chart or multiple flows and/or block diagram one The step of function of being specified in a square frame or multiple square frames.
Although preferred embodiments of the present invention have been described, but those skilled in the art once know basic creation Property concept, then can make these embodiments other change and modification.So appended claims be intended to be construed to include it is excellent Select embodiment and fall into all change and modification of the scope of the invention.
Obviously, various changes and modifications can be made to the invention without departing from essence of the invention by those skilled in the art God and scope.In this way, if these modifications and changes of the present invention belongs to the scope of the claims in the present invention and its equivalent technologies Within, then the present invention is also intended to comprising including these modification and variations.

Claims (12)

  1. A kind of 1. interpretation method based on SOVA decoder algorithm SOVA, it is characterised in that the described method includes：
    Using viterbi algorithm, in the grid chart of setting, the corresponding maximum likelihood path of receiving sequence is determined, and described in calculating The metric difference of the contended path of each state node and the maximum likelihood path, the grid chart are used in maximum likelihood path Characterize the state change of encoder at different moments；
    According to the value of the metric difference, from the state node in the maximum likelihood path, K state node is selected to be determined as Sampled point, K are positive integer；
    Using the sampled point as backtracking node, backtracking process is carried out, to update each information ratio that the receiving sequence includes Special log-likelihood ratio LLR value.
  2. 2. the method as described in claim 1, it is characterised in thatThe L is the corresponding information of the receiving sequence The length of bit, the M are the downsampling factor of setting,Expression rounds up computing.
  3. 3. method as claimed in claim 1 or 2, it is characterised in that according to the value of the metric difference, from the maximum likelihood road In state node on footpath, K state node is selected to be determined as sampled point, including：
    The metric difference is ranked up according to order from small to large, the metric difference that selected and sorted position is located at preceding K corresponds to State node be determined as sampled point；Or
    The metric difference is divided into P groups, according to the value of every group of metric difference, at least one metric difference is selected from every group of metric difference Corresponding states node is determined as sampled point, and the P is positive integer.
  4. 4. method as claimed in claim 3, it is characterised in that the metric difference is divided into P groups, including：
    According to the numbering of the metric difference, the metric difference is divided into P groups successively, the numbering of every group of metric difference included connects It is continuous；Or
    According to the numbering of the metric difference, the metric difference numbered at intervals of P is divided into one group successively.
  5. 5. method as claimed in claim 4, it is characterised in that the value of the P is K；Or
    The value of the P isThe L is the length of the corresponding information bit of the receiving sequence, and n is positive integer, M For the downsampling factor of setting,Expression rounds up computing.
  6. 6. method as claimed in claim 5, it is characterised in that according to the value of every group of metric difference, selected from every group of metric difference At least one metric difference corresponding states node is determined as sampled point, including：
    If the value of the P is K, according to the value of the metric difference, from every group of metric difference, the metric difference of minimum is selected to correspond to shape State node is determined as sampled point；Or
    If the value of the P isFrom every group of metric difference, selected metric difference is according to before being arranged sequentially from small to large The corresponding state node of metric difference of n is determined as sampled point.
  7. 7. a kind of code translator based on SOVA decoder algorithm SOVA, it is characterised in that described device includes：
    Path determination module, for using viterbi algorithm, in the grid chart of setting, determining the corresponding maximum of receiving sequence seemingly Right path, and calculate the measurement of the contended path of each state node and the maximum likelihood path in the maximum likelihood path Difference, the grid chart are used for the state change for characterizing encoder at different moments；
    Sampling module, for the value according to the metric difference, from the state node in the maximum likelihood path, selects K State node is determined as sampled point, and K is positive integer；
    Backtracking module, for using the sampled point as backtracking node, carrying out backtracking process, being included with updating the receiving sequence Each information bit log-likelihood ratio LLR value.
  8. 8. device as claimed in claim 7, it is characterised in thatThe L is the corresponding information of the receiving sequence The length of bit, the M are the downsampling factor of setting,Expression rounds up computing.
  9. 9. device as claimed in claim 7 or 8, it is characterised in that the sampling module is specifically used for：
    The metric difference is ranked up according to order from small to large, the metric difference that selected and sorted position is located at preceding K corresponds to State node be determined as sampled point；Or
    The metric difference is divided into P groups, according to the value of every group of metric difference, at least one metric difference is selected from every group of metric difference Corresponding states node is determined as sampled point, and the P is positive integer.
  10. 10. device as claimed in claim 9, it is characterised in that the sampling module is specifically used for：
    According to the numbering of the metric difference, the metric difference is divided into P groups successively, the numbering of every group of metric difference included connects It is continuous；Or
    According to the numbering of the metric difference, the metric difference numbered at intervals of P is divided into one group successively.
  11. 11. device as claimed in claim 10, it is characterised in that the value of the P is K；Or
    The value of the P isThe L is the length of the corresponding information bit of the receiving sequence, and n is positive integer, and M is The downsampling factor of setting,Expression rounds up computing.
  12. 12. device as claimed in claim 11, it is characterised in that the sampling module is specifically used for：
    If the value of the P is K, according to the value of the metric difference, from every group of metric difference, the metric difference of minimum is selected to correspond to shape State node is determined as sampled point；Or
    If the value of the P isFrom every group of metric difference, selected metric difference is according to before being arranged sequentially from small to large The corresponding state node of metric difference of n is determined as sampled point.
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