CN113765624A - TPC iterative decoding method and device, telemetering ground station and storage medium - Google Patents
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- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04L1/0047—Decoding adapted to other signal detection operation
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- H03M13/29—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 combining two or more codes or code structures, e.g. product codes, generalised product codes, concatenated codes, inner and outer codes
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Abstract
The invention discloses a TPC iterative decoding method, which comprises the following steps: hard decision is carried out on input soft information, and p least reliable code element positions are found out; exhaustive p least reliable symbol positions, obtain 2pGenerating a test sequence by using the test pattern; algebraic decoding is carried out on the test sequence, and the obtained effective code words are classified into a subcode set omega; judging whether an effective code word corresponding to the input soft information in the sub-code set omega has an error or not; determining a decision codeword array in a subcode set omega; calculating external information according to the decision codeword array, and updating the input soft information by using the external information; and if the iteration times are not reached, carrying out next iteration, and if the iteration times are reached, outputting a hard judgment of an iteration result. The invention also discloses a TPC decoding device, a telemetering ground station and a storage medium. The invention can effectively reduce the computation amount of TPC iterative decoding and save resources.
Description
Technical Field
The invention belongs to the technical field of channel coding, and particularly relates to a TPC iterative decoding method, a TPC iterative decoding device, a telemetering ground station and a storage medium.
Background
With the rapid development of the communication industry, people have higher and higher requirements for high-quality communication. Therefore, in modern digital communication research, how to reduce the complexity of the algorithm and improve the data transmission efficiency on the premise of ensuring the transmission quality becomes the direction of efforts of engineers. TPC coding is widely used in the field of wireless communication because of its excellent data error correction capability.
The existing TPC soft information decoding mostly adopts a processing flow of CHASE decoding and iterative operation, and has the disadvantages of higher algorithm complexity, larger operation amount, high code rate requirement or less resource processing chip which is not suitable for use.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a TPC iterative decoding method, a TPC iterative decoding device, a telemetering ground station and a storage medium, wherein the TPC iterative decoding method can effectively reduce the operation amount.
A TPC iterative decoding method, comprising:
s1: hard decision is carried out on input soft information, and p least reliable code element positions are found out;
s2: exhaustively enumerating the p least reliable symbol positions, obtaining 2pGenerating a test sequence by using the test pattern;
s3: algebraic decoding is carried out on the test sequence, and the obtained effective code words are classified into a subcode set omega;
s4: judging whether an effective code word corresponding to the input soft information in the sub-code set omega is wrong or not, if so, executing a step S5, otherwise, mapping the effective code word into the maximum soft information as the input soft information for iteration, and executing a step S7;
s5: determining a decision codeword array d in a subcode set omegai；
S6: according to the decision code word array diComputing extrinsic information wiAnd using said extrinsic information wiUpdating the initial input soft information to obtain input soft information for iteration;
s7: if the iteration times are not reached, returning to execute the step S1; and if the iteration times are reached, outputting the hard judgment of the iteration result.
Preferably, the decision codeword array d is determined in the sub-code set ΩiThe method comprises the following steps:
performing correlation calculation on the effective code words in the sub-code set omega, and determining the effective code words with the maximum correlation degree with the input soft information as the decision code word array di。
As a preferred scheme, the decision codeword array d is obtained according to the decisioniComputing extrinsic information wiThe method comprises the following steps:
wherein
As a preferred scheme, the decision codeword array d is obtained according to the decisioniComputing extrinsic information wiThe method comprises the following steps:
wi＝ref×di,
where ref is a constant.
Preferably, the external information w is utilizediUpdating the initial input soft information, comprising:
[R(m)]＝[R]+[W(m)]。
a TPC decoding apparatus comprising:
the input soft information storage module is used for storing input soft information required by decoding each time;
the unreliable bit calculation module is used for carrying out hard decision on the input soft information and finding out p least reliable code element positions;
a test sequence generating module, configured to exhaust the p least reliable symbol positions, obtain 2p test patterns, and generate a test sequence;
the algebraic decoding module is used for algebraically decoding the test sequence and classifying the obtained effective code words into a subcode set omega;
the reliability judging module is used for judging whether an error occurs in an effective code word corresponding to the input soft information in the sub-code set omega;
a maximum soft information output module, configured to map the effective codeword corresponding to the input soft information into maximum soft information when the error does not occur, where the maximum soft information is used as input soft information for iteration;
a decision codeword determining module, configured to determine a decision codeword array d in the sub-code set Ω when the error occursi；
An extrinsic information calculation module for calculating the decision codeword array diComputing extrinsic information wiThe external information wiUpdating the initial input soft information;
the iteration judging module is used for judging whether the iteration times are reached, if not, the updated input soft information is sent to the input soft information storage module, and if so, the iteration result is sent to the iteration result output module;
and the iteration result output module is used for outputting the iteration result hard decision.
A telemetry ground station, comprising:
a processor;
a storage device having a program stored thereon;
when executed by the processor, cause the processor to implement any of the TPC iterative decoding methods as described above.
A computer readable storage medium having stored thereon a computer program, wherein the program when executed by a processor implements a TPC iterative decoding method as any one of the preceding.
Compared with the prior art, the invention has the following beneficial effects:
1. by adding a judgment flow after algebraic decoding, the maximum soft information is directly mapped and output under the condition that the effective code words corresponding to the input soft information have no error code, and the reliability of the position is ensured during next iteration; time loss of an extrinsic information calculation process is reduced, the operation amount is reduced, the possibility that the position of the code word is judged to be unreliable in the next iteration process is eliminated, and the accuracy of decoding error correction is improved;
2. by simplifying the Euclidean distance in the extrinsic information calculation method into related calculation and simplifying the multiplication into mapping and addition and subtraction for processing, the resource consumption of the algorithm is reduced on the basis of ensuring the decoding error correction performance.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic flow chart of a TPC iterative decoding method according to the present invention;
FIG. 2 is a comparison graph of the performance of the TPC iterative decoding method of the present invention and the prior art;
fig. 3 is a schematic structural diagram of a TPC decoding apparatus according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In a first aspect, as shown in fig. 1, a TPC soft information decoding method includes:
s1: for the hard decision of the input soft information, p least reliable symbol positions are found.
In the step, an acceptance sequence Y is obtained by hard decision of input soft information, and the reliability of each code element in Y is determined; in the receiving sequence Y, determining p least reliable symbol positions, wherein the value of p is not more than the number of information bits in the sequence.
S2: exhaustively enumerating the p least reliable symbol positions, obtaining 2pTest patterns and test sequences are generated.
In this step, a permutation and combination structure q is 2 based on the p least reliable symbol positionspA test pattern Tq(ii) a Generating a test sequence Zq＝Y⊕TqAnd ∈ denotes a modulo-2 sum operation, i.e., an exclusive or.
S3: and carrying out algebraic decoding on the test sequence, and classifying the obtained effective code words into a subcode set omega.
In this step, algebraic decoder is used to test sequence ZqPerforming hard decision decoding, comprising the steps of: calculating a syndrome; obtaining the error occurrence position by utilizing the syndrome; turning over the number corresponding to the error occurrence position; the obtained effective code word CiFall under the subcode set omega.
S4: and judging whether the effective code words corresponding to the input soft information in the sub-code set omega are wrong or not, if so, executing step S5, otherwise, mapping the effective code words into the maximum soft information to be used as the input soft information for iteration, and executing step S7.
In this step, there are 2 in the sub-code set ΩpAnd one effective code word corresponding to the receiving sequence Y (other effective code words are obtained by permutation and combination construction in the test sequence) is obtained by directly and hard judging input soft information and then performing algebraic decoding. Judging the effective code word, if no error exists in algebraic decoding, mapping the effective code word into maximum soft information as output (for example, if the data range of the input soft information is-255- +255, mapping the code source 1 in the effective code word to +255, and mapping the code source 0 to-255), and obtaining the input soft information for the next iteration; if the error exists, the subsequent steps are continuously executed. The purpose of mapping the effective code words into the maximum soft information is to avoid selecting the position as an unreliable position in the subsequent iteration process, and simultaneously, the decoding skips the calculation process of the external information, so that the calculation period of the algorithm can be shortened.
S5: determining a decision codeword array d in a subcode set omegai。
In this step, the euclidean distance between the effective codeword in the sub-code set Ω and the input soft information may be calculated, and the decision codeword array d having the minimum euclidean distance may be foundi. In addition, the decision codeword array diThe code word can be found not only by calculating the euclidean distance, but also by correlation calculation, and can be a valid code word with the minimum euclidean distance to the input soft information, or a valid code word with the maximum correlation to the input soft information.
S6: according to the decision code word array diComputing extrinsic information wiAnd using the extrinsic informationwiAnd updating the input soft information to obtain the input soft information for the next iteration.
In this step, the extrinsic information wiCan be calculated by a conventional calculation formula:
the extrinsic information wiThe traditional method for updating the input soft information is as follows:
[R(m)]＝[R]+α(m)[W(m)] ②；
wherein R represents initial input soft information, R (m) represents iterative input soft information, D represents decision codeword, C represents competition codeword, D represents decision codeword, andirepresenting an array of decision codewords, riRepresenting the initial input soft information, ri' represents the output soft information of the decoder; alpha (m) and beta are specific arrays and are iteration factors of the TPC decoder, wherein the alpha (m) array is a weight factor, and the value of the weight factor increases with the iteration number; the beta array is a reliability factor, the value of which increases with the number of iterations.
S7: if the iteration times are not reached, returning to execute the step S1; and if the iteration times are reached, outputting the hard judgment of the iteration result.
In this embodiment, a chase-2 algorithm and a SISO iterative decoding algorithm are adopted. In the iterative decoding in this embodiment, the decoding operations in steps S1-S7 are performed on the row code words and the column code words in turn, and either the row code words or the column code words are decoded in one iteration; these matters belong to the prior art and are not described herein. The number of iterations may be selected to be 4.
The invention adds a judgment flow after algebraic decoding, directly maps and outputs the maximum soft information under the condition that the effective code word (original subcode) corresponding to the input soft information has no error code, and ensures the reliability of the position when the next iteration is carried out; the time loss of the extrinsic information calculation process is reduced, the operation amount is reduced, the possibility that the position of the code word is judged to be unreliable in the next iteration process is eliminated, and the accuracy of decoding error correction is improved.
Fig. 2 is an MATLAB simulation diagram comparing the performance of the TPC iterative decoding algorithm of the present invention with that of the prior art, in which the performance of the TPC iterative decoding algorithm of the present invention is improved compared with the conventional algorithm under the same condition (4 iterations, 2 bits are selected for unreliable positions); at a bit error rate of 10-5Under the condition, when the TPC soft information decoding performance is compared with that without coding gain, the performance is improved by about 6.5 dB; compared with the traditional TPC soft information decoding process, the performance is improved by about 0.5 dB.
In one embodiment, the decision codeword array diMay be determined by correlation calculations rather than euclidean distance calculations. Specifically, the decision codeword array d is determined in the sub-code set Ω in S5iThe method comprises the following steps:
performing correlation calculation on the effective code words in the sub-code set omega to obtain the effective code words with the maximum correlation degree with the input soft information;
determining the effective code word with the maximum correlation degree as the decision code word array di。
The following describes a method of replacing the euclidean distance calculation with the correlation calculation:
the calculation formula of Euclidean distance is developed as follows:
said formula III
I.e. ciFrom {0,1} is mapped to { -1,1}, ciIs an array of valid codewords. Wherein
And
is a constant term;
is R and CiIn (2)Product, i.e. input of soft information R and valid code word CiThe correlation value of (2). Therefore, finding the valid codeword with the minimum euclidean distance can be converted into finding the valid codeword with the maximum correlation value.
Further, the correlation value of the decision codeword D with the input soft information R can be expressed as:
when there is a competing codeword C in the sub-code set Ω, the correlation value of the competing codeword C and the input soft information R can be represented as:
in the formulas (i) and (v), the multiplication is replaced by 0/1 judgment for calculating the correlation value, the judgment codeword D and the competition codeword C after algebraic decoding are judged, the input soft information is accumulated if the judgment codeword D and the competition codeword C are 1, and the input soft information after negation is accumulated if the judgment codeword D and the competition codeword C are 0. Thus, the resource consumption and the calculation amount can be further reduced, and a higher code rate or a chip with less resources can be adopted.
On the basis of the foregoing embodiment, further, according to the decision codeword array diComputing extrinsic information wiThe method comprises the following steps: will output soft information ri' as extrinsic information wiFrom this, it can be derived that the extrinsic information w is when there is a competing codeword C in the sub-code set Ω (C ∈ Ω)iThe value of (c):
in this embodiment, the calculation of the extrinsic information also uses a decision method, if di1 then the codeword correlation value d is decidedDSubtracting the competitive codeword correlation value dCAnd if the value is 0, competing code word correlation value dCSubtracting the decision codeword correlation value dD. Compared with the traditional extrinsic information calculation formula (I), the method isAnd the Euclidean distance is simplified into related calculation, and multiplication is also simplified into mapping and addition and subtraction for processing, so that the resource consumption of the algorithm is reduced on the basis of ensuring the decoding error correction performance.
As a further optimization, the extrinsic information w is when there is no competing codeword C in the set Ω of sub-codesiThe value of (b) may be considered to replace the beta array in the conventional extrinsic information calculation formula (r) with a constant ref, i.e.:
thus, the calculation amount can be further simplified, and the efficiency can be improved. For example, if the input soft information has a value in the range of-255 to 255, the constant ref can be set to 128.
As a further optimization, the utilization of the extrinsic information wiThe method for updating the input soft information comprises the following steps:
[R(m)]＝[R]+[W(m)] ⑧。
in this embodiment, the weighting factor α (m) in the formula of the conventional input soft information updating method is further removed, and the calculated extrinsic information is directly added to the initial input soft information to serve as new input soft information. This further simplifies the computation, while still the decoding performance can be guaranteed. In the prior art, if the weight factor is directly removed, the decoding performance is influenced; in the scheme of this embodiment, even if the weighting factor is removed, the decoding performance is not affected, and the calculation is faster.
In a second aspect, as shown in fig. 3, a TPC decoding apparatus includes:
the input soft information storage module is used for storing input soft information required by decoding each time;
the unreliable bit calculation module is used for carrying out hard decision on the input soft information and finding out p least reliable code element positions;
a test sequence generating module, configured to exhaust the p least reliable symbol positions, obtain 2p test patterns, and generate a test sequence;
the algebraic decoding module is used for algebraically decoding the test sequence and classifying the obtained effective code words into a subcode set omega;
the reliability judging module is used for judging whether an error occurs in an effective code word corresponding to the input soft information in the sub-code set omega;
a maximum soft information output module, configured to map the effective codeword corresponding to the input soft information into maximum soft information when the error does not occur, where the maximum soft information is used as input soft information for a next iteration;
a decision codeword determining module, configured to determine a decision codeword array d in the sub-code set Ω when the error occursi；
An extrinsic information calculation module for calculating the decision codeword array diComputing extrinsic information wiThe external information wiThe soft information updating module is used for updating the initial input soft information to obtain input soft information for the next iteration;
the iteration judging module is used for judging whether the iteration times are reached, if not, the updated input soft information is sent to the input soft information storage module, and if so, the iteration result is sent to the iteration result output module;
and the iteration result output module is used for outputting the iteration result hard decision.
The input soft information storage module is used for storing input soft information, and the input soft information comprises initial input soft information and updated iterative input soft information. The initial input soft information is used for calculating the correlation degree and the extrinsic information, and the soft information is output when the original subcode is wrong. And the iteration input soft information is used for searching an unreliable position and judging whether an error occurs.
In one embodiment, the storing of the input soft information uses ping-pong caching. Therefore, the cache space can be saved, and the real-time processing of the data can be realized.
The present invention also provides a telemetry ground station comprising:
a processor;
a storage device having a program stored thereon;
when executed by the processor, cause the processor to implement any of the TPC iterative decoding methods of the first aspect.
Wherein the processor and the storage device may be implemented by an FPGA, and the program may be an embedded program.
The present invention also provides a computer readable storage medium having a computer program stored thereon, wherein the program, when executed by a processor, implements a TPC iterative decoding method as any one of the first aspects.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above examples are merely illustrative of several embodiments of the present invention, and the description thereof is more specific and detailed, but not to be construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present invention should be subject to the appended claims.
Claims (8)
1. A TPC iterative decoding method, comprising:
s1: hard decision is carried out on input soft information, and p least reliable code element positions are found out;
s2: exhaustively enumerating the p least reliable symbol positions, obtaining 2pGenerating a test sequence by using the test pattern;
s3: algebraic decoding is carried out on the test sequence, and the obtained effective code words are classified into a subcode set omega;
s4: judging whether an effective code word corresponding to the input soft information in the sub-code set omega is wrong or not, if so, executing a step S5, otherwise, mapping the effective code word into the maximum soft information as the input soft information for iteration, and executing a step S7;
s5: determining a decision codeword array d in a subcode set omegai；
S6: according to the decision code word array diComputing extrinsic information wiAnd using said extrinsic information wiUpdating the initial input soft information to obtain input soft information for iteration;
s7: if the iteration times are not reached, returning to execute the step S1; and if the iteration times are reached, outputting the hard judgment of the iteration result.
2. The TPC iterative decoding method of claim 1, wherein:
determining a decision codeword array d in the sub-code set omegaiThe method comprises the following steps:
performing correlation calculation on the effective code words in the sub-code set omega, and determining the effective code words with the maximum correlation degree with the input soft information as the decision code word array di。
3. The TPC iterative decoding method of claim 2, wherein:
the method according to the decision codeword array diComputing extrinsic information wiThe method comprises the following steps:
wherein
4. The TPC iterative decoding method of claim 3, wherein:
the method according to the decision codeword array diComputing extrinsic information wiThe method comprises the following steps:
5. The TPC iterative decoding method of any one of claims 3 or 4 wherein:
said utilizing said extrinsic information wiUpdating the initial input soft information, comprising:
[R(m)]＝[R]+[W(m)]。
6. a TPC decoding apparatus, comprising:
the input soft information storage module is used for storing input soft information required by decoding each time;
the unreliable bit calculation module is used for carrying out hard decision on the input soft information and finding out p least reliable code element positions;
a test sequence generating module, configured to exhaust the p least reliable symbol positions, obtain 2p test patterns, and generate a test sequence;
the algebraic decoding module is used for algebraically decoding the test sequence and classifying the obtained effective code words into a subcode set omega;
the reliability judging module is used for judging whether an error occurs in an effective code word corresponding to the input soft information in the sub-code set omega;
a maximum soft information output module, configured to map the effective codeword corresponding to the input soft information into maximum soft information when the error does not occur, where the maximum soft information is used as input soft information for iteration;
a decision codeword determining module, configured to determine a decision codeword array d in the sub-code set Ω when the error occursi；
An extrinsic information calculation module for calculating the decision codeword array diComputing extrinsic information wiThe external information wiUpdating the initial input soft information;
the iteration judging module is used for judging whether the iteration times are reached, if not, the updated input soft information is sent to the input soft information storage module, and if so, the iteration result is sent to the iteration result output module;
and the iteration result output module is used for outputting the iteration result hard decision.
7. A telemetry ground station, comprising:
a processor;
a storage device having a program stored thereon;
when executed by the processor, cause the processor to implement the TPC iterative decoding method of any of claims 1-5.
8. A computer readable storage medium having stored thereon a computer program, wherein the program when executed by a processor implements the TPC iterative decoding method of any of claims 1 to 5.
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| EP1976128A1 (en) * | 2007-03-30 | 2008-10-01 | Hitachi Global Storage Technologies Netherlands B.V. | Techniques for correcting errors using iterative decoding |
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Application publication date: 20211207 |