CN114221664A - Low-complexity polar code simplified soft elimination list decoder and decoding method - Google Patents
Low-complexity polar code simplified soft elimination list decoder and decoding method Download PDFInfo
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Abstract
The invention discloses a low-complexity decoding device and a decoding method for a simplified soft elimination list of a polar code. The invention comprises the following steps: a parameter configuration module for providing the required information for the following module before the decoding starts; a permutation arrangement selection module for providing a required set of permutation arrangements for subsequent modules; the preprocessing module is used for carrying out corresponding replacement on the channel receiving information according to the replacement arrangement set; a plurality of simplified soft elimination decoding modules with the same factor graph form are used for decoding in parallel, and each simplified soft elimination decoding module comprises an initialization sub-module, an iterative decoding sub-module and a decoding bit judgment sub-module; and the decision device module is used for selecting the decoding sequence corresponding to the minimum path metric value and extracting the initial information sequence from the decoding sequence. The invention solves the technical problem that the soft elimination list decoder in the prior art has high computational complexity, and reduces the computational complexity of the soft elimination list decoder.
Description
Technical Field
The invention belongs to the technical field of channel coding, and relates to a low-complexity decoding device and a decoding method for a simplified soft elimination list of a polarization code.
Background
Polar codes are a class of linear error correcting codes that are mathematically proven to achieve channel capacity when their code length is close to infinity. The polar code coding scheme has been adopted as a coding method for a control channel of a fifth generation communication system in the discussion of the 87 th meeting in the RANI, and has wide application in very large scale machine communication (mtc), ultra-reliable low-latency (URRLC) communication and enhanced mobile broadband communication (eMBB).
The polar code decoders currently in the mainstream can be classified into two categories according to their decoding outputs, namely hard output decoders and soft output decoders. The polar code hard output decoder is used for directly judging the information transmission bit according to the received signal, and the polar code soft output decoder is used for calculating the soft information value of the transmitted information according to the received signal and then carrying out hard judgment on the soft information value. Therefore, the soft output decoder has better flexibility and adaptability. Currently, a polar code hard output decoder mainly includes a Successive Cancellation (SC) decoder, a Successive Cancellation List (SCL) decoder, and a CRC-assisted successive cancellation list (CA-SCL) decoder, and a polar code soft output decoder mainly includes a Belief Propagation (BP) decoder, a Soft Cancellation (SCAN) decoder, and a soft cancellation list (SCANL) decoder. In terms of decoding performance, the performance of the SC decoder is the worst, the BP decoder and the SCAN decoder have similar performance and are superior to the SC decoder, and the performance of the SCANL decoder is greatly improved compared with the former three, but is not as good as that of the SCL decoder and the CA-SCL decoder.
In some 5G scene applications, the decoder is required to output soft information, so that the purpose of outputting soft information can be achieved only by using soft output decoders such as a BP decoder, a SCAN decoder, a scall decoder and the like in this case. Although the performance of the SCANL decoder is good, the calculation complexity is high, and the SCANL decoder is difficult to realize in practical application. Therefore, how to design a decoder which can maintain the high decoding performance of the SCANL decoder and reduce the computational complexity of the SCANL decoder is a technical problem to be solved at present.
Disclosure of Invention
An object of the present invention is to solve the problem of high computational complexity of the soft erasure list decoder in the prior art, and to provide a low-complexity polarization code simplified soft erasure list decoder for reducing the computational complexity of the soft erasure list decoder.
The decoder of the present invention includes: the device comprises a parameter configuration module, a permutation and arrangement selection module, a preprocessing module, a plurality of simplified soft elimination decoding modules and a decision device module; the simplified soft cancellation decoding module includes: initializing a sub-module, iterating a decoding sub-module and decoding a bit judgment sub-module;
the parameter configuration module is used for providing required information for the subsequent module before decoding begins;
the permutation and arrangement selection module is used for providing a required permutation and arrangement set for a subsequent module;
the preprocessing module is used for carrying out corresponding replacement on the channel receiving information according to the replacement arrangement set;
the simplified soft elimination decoding modules have the same factor graph form, and the simplified soft elimination decoding modules decode in parallel, wherein: the initialization sub-module carries out initial parameter setting on the decoding factor graph; the iterative decoding submodule is used for soft information updating and transmitting operation, decoding nodes are deleted, and nodes in a factor graph are classified by taking initial parameters set on nodes corresponding to freezing positions in the initialization submodule as standards; the decoding bit decision submodule is used for acquiring decoding sequence information;
the decision device module is used for selecting the decoding sequence corresponding to the minimum path metric value and taking out the initial information sequence from the decoding sequence.
Another object of the present invention is to provide a decoding method of the decoder. The method comprises the following specific steps:
step (1) inputs given polarization code parameter information (N, K, F) and received channel log likelihood ratio information LLRs into a parameter configuration module, wherein LLRs is { LLR }0,LLR1,…,LLRN-1Determining index information pos as (0,1, …, N-1) according to the channel log-likelihood ratio information LLRs, wherein N represents a polar code length, K represents an initial information sequence length, F represents a frozen bit index set, and the length is N-K;
and performing parameter configuration according to the polarization code parameter information, the channel log-likelihood ratio information and the index information, and inputting all information into an information storage unit in a parameter configuration module for a subsequent module to read at any time.
Step (2) the permutation and arrangement selection module reads index information from the parameter configuration module and defines the arrangement pi with the length of N 00,1, …, N-1 }; will arrange pi0The middle elements are arranged and combined to obtain N! In different arrangements i.e. { π0,π1,…,πN!-1Comparing Hamming distances among the arrays, selecting the first L arrays with large Hamming distances to form an array set pi (pi) ═ pi0,π1,…,πL-1}。
And (3) reading the permutation set pi (pi) ═ pi in the permutation and arrangement selection module by the preprocessing module0,π1,…,πL-1And polarization code parameter information (N, K, F) and channel log likelihood ratio information LLRs ═ LLR { (LLR) } in the parameter configuration module0,LLR1,…,LLRN-1And permutation is performed on the LLRs according to the permutation set pi (pi), and a permutation log likelihood ratio information set pi (LLRs) is obtained0,LLRs1,…,LLRsL-1}=Π[π(LLRs)]。
And (4) correspondingly inputting elements in the replacement log-likelihood ratio information set Π (LLRs) into L simplified soft elimination decoding modules with the same factor graph form for parallel decoding, and reading the polarization code parameter information (N, K and F) from the preprocessing module by the simplified soft elimination decoding modules. Wherein:
(4-1) the initialization submodule carries out initial parameter setting on the decoding factor graph by utilizing the permutation log likelihood ratio information and the polarization code parameter information (N, K, F), and sets left information lambda on the rightmost column node of the decoding factor graphi nThe initial parameter is the information of the replacement log likelihood ratio, and the right information beta on the node corresponding to the freezing position of the leftmost column of the factor graph is seti 0The initial parameter gamma is a positive integer, and the right information initial parameters on the other nodes are set to be 0:i is more than or equal to 0 and less than or equal to N-1, and F is a frozen bit index set;
(4-2) the iterative decoding submodule carries out soft information updating and transmitting operation based on a decoding factor graph structure, and simplification is carried out by deleting decoding nodes in the soft information updating process;
calculating a path metric value PM, initializing the PM to be 0, and updating the path metric value when a node corresponding to a frozen bit is encountered, wherein the rule is updatedComprises the following steps: PM- λi,i∈F,λiLeft information on the corresponding node of the frozen bit; when the left information and the right information respectively reach the left side and the right side of the decoding factor graph, the iterative decoding submodule completes decoding to obtain path metric value information;
(4-3) the decoding bit decision sub-module carries out bit decision operation according to the soft information on the leftmost node of the decoding factor graph, and the decoding sequence of the ith nodeλi 0、βi 0Left and right information on the node, respectively.
Step (5) when the parallel decoding of the L simplified soft elimination decoding modules is completed, the decision device module reads the decoding sequence information and the corresponding path metric value information from the L simplified soft elimination decoding modules in sequence and uses the decoding sequence set to collectAnd the path metric set Pi (PM) { PM }0,PM1,…,PML-1Storing in the form of II, selecting the smallest path metric value PM in II (PM) setmin=min{PM0,…,PML-1According to the minimum path metric value PMminAt index positions in the collection, obtaining the collectionCoding sequence of middle corresponding index position
Step (6) from the decoded sequenceTaking out K bit long initial information sequenceAnd finishing decoding.
Further, in the step (2),array piaAnd pibHamming distance therebetweenδ is the kronecker pulse function.
Further, the simplification by the decoding node deletion described in (4-2) is specifically as follows,for the value of the soft information to be transferred, t is more than or equal to 0 and less than or equal to (log)2N-1):
(a) If nodeAnd nodeUpper right informationAll are less than gamma, then the node is judgedAnd nodeIs an information bit node; the soft information updating calculation process comprises the following steps:
(b) If nodeUpper right informationNode pointUpper right informationThen the decision nodeTo freeze a bit node, a nodeIs an information bit node; and betai tThe related soft information updating calculation process is simplified as follows:
(c) if nodeUpper right informationNode pointUpper right informationThen the decision nodeBeing information bit nodes, nodesIs a frozen bit node; andthe related soft information updating calculation process is simplified as follows:
(d) if nodeAnd nodeUpper right informationAre all more than or equal to gamma, then the node is judgedAnd nodeIs a frozen bit node; the soft information updating calculation process comprises the following steps:
compared with the prior art, the invention has the following beneficial effects: the decoding module in the soft elimination list decoder is improved by using a decoding node deleting technology, the calculation process related to the soft information on the frozen bit node in the decoding process is simplified, and the frozen bit node is approximately deleted, so that the calculation complexity of the decoder is reduced.
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FIG. 1 is a schematic diagram of a decoder according to the present invention;
FIG. 2 is a diagram illustrating initial parameter settings in an initialization submodule;
FIG. 3 is a diagram of soft information transfer in a soft erasure coding unit factor graph;
Detailed Description
The technical scheme of the invention is further specifically described by the following embodiments and the accompanying drawings.
A low complexity decoding method for simplified soft erasure list of polar codes, using a decoder as shown in fig. 1, comprising: the device comprises a parameter configuration module, a permutation and arrangement selection module, a preprocessing module, a plurality of simplified soft elimination decoding modules and a decision device module; the simplified soft cancellation decoding module includes: the device comprises an initialization sub-module, an iterative decoding sub-module and a decoding bit judgment sub-module.
The parameter configuration module is used for providing required information for the subsequent module before decoding begins;
the permutation and arrangement selection module is used for providing a required permutation and arrangement set for a subsequent module;
the preprocessing module is used for carrying out corresponding replacement on the channel receiving information according to the replacement arrangement set;
the simplified soft elimination decoding modules have the same factor graph form, and the simplified soft elimination decoding modules decode in parallel, wherein: the initialization sub-module carries out initial parameter setting on the decoding factor graph; the iterative decoding submodule is used for soft information updating and transmitting operation, decoding nodes are deleted, and nodes in a factor graph are classified by taking initial parameters set on nodes corresponding to freezing positions in the initialization submodule as standards; the decoding bit decision submodule is used for acquiring decoding sequence information;
the decision device module is used for selecting the decoding sequence corresponding to the minimum path metric value and taking out the initial information sequence from the decoding sequence.
The specific decoding method is as follows:
step (1) inputs given polarization code parameter information (N, K, F) and received channel log likelihood ratio information LLRs into a parameter configuration module, wherein LLRs is { LLR }0,LLR1,…,LLRN-1Determining index information pos as (0,1, …, N-1) according to the channel log-likelihood ratio information LLRs, wherein N represents a polar code length, K represents an initial information sequence length, F represents a frozen bit index set, and the length is N-K;
and performing parameter configuration according to the polarization code parameter information, the channel log-likelihood ratio information and the index information, and inputting all information into an information storage unit in a parameter configuration module for a subsequent module to read at any time.
Step (2) the permutation and arrangement selection module reads index information from the parameter configuration module and defines the arrangement pi with the length of N 00,1, …, N-1 }; will arrange pi0The middle elements are arranged and combined to obtain N! In different arrangements i.e. { π0,π1,…,πN!-1Comparing Hamming distances among the arrays, selecting the first L arrays with large Hamming distances to form an array set pi (pi) ═ pi0,π1,…,πL-1}; array piaAnd pibHamming distance therebetweenδ is the kronecker pulse function.
And (3) reading the permutation set pi (pi) ═ pi in the permutation and arrangement selection module by the preprocessing module0,π1,…,πL-1And polarization code parameter information (N, K, F) and channel log likelihood ratio information LLRs ═ LLR { (LLR) } in the parameter configuration module0,LLR1,…,LLRN-1And permutation is performed on the LLRs according to the permutation set pi (pi), and a permutation log likelihood ratio information set pi (LLRs) is obtained0,LLRs1,…,LLRsL-1}=Π[π(LLRs)]。
And (4) correspondingly inputting elements in the replacement log-likelihood ratio information set Π (LLRs) into L simplified soft elimination decoding modules with the same factor graph form for parallel decoding, and reading the polarization code parameter information (N, K and F) from the preprocessing module by the simplified soft elimination decoding modules. The simplified soft cancellation decoding module includes: the device comprises an initialization sub-module, an iterative decoding sub-module and a decoding bit judgment sub-module.
The initialization submodule carries out initial parameter setting on the decoding factor graph by utilizing the permutation log likelihood ratio information and the polarization code parameter information (N, K, F). Taking the decoding factor graph shown in fig. 2 as an example, the initialization sub-module sets left information λ on the rightmost column node of the decoding factor graphi nThe initial parameter is the information of the replacement log likelihood ratio, and the right information beta on the node corresponding to the freezing position of the leftmost column of the factor graph is seti 0The initial parameter gamma is a positive integer, and the right information initial parameters on the other nodes are set to be 0:i is more than or equal to 0 and less than or equal to N-1, and F is a frozen bit index set.
And after the initialization setting is completed, the iterative decoding submodule starts to operate. The iterative decoding submodule carries out soft information updating and transmitting operation based on a decoding factor graph structure, and a decoding node deleting technology is adopted to simplify the soft information updating process. The decoding node deletion technique is described below, taking the decoding unit factor graph shown in FIG. 3 as an example, where delivery is required Four soft information values, t is more than or equal to 0 and less than or equal to (log)2N-1), the remaining soft information values are known. And classifying the nodes in the unit factor graph according to the initial parameter gamma set on the nodes corresponding to the freezing bits in the initialization submodule. The frozen bit nodes are represented as black nodes, the information bit nodes are represented as white nodes, and the non-decision nodes are represented as shaded nodes. Nodes in the unit factor graph shown in FIG. 3And nodeUpper right informationFor the soft information sought, its value is unknown, so the nodeAnd nodeI.e. non-decision nodes and represented by shaded nodes, and nodesAnd nodeUpper right informationAre known, and therefore can be paired with nodesAnd nodeThe classification decision is made as follows:
(a) if nodeAnd nodeUpper right informationAll are less than gamma, then the node is judgedAnd nodeIs an information bit node; the soft information updating calculation process comprises the following steps:
(b) If nodeUpper right informationNode pointUpper right informationThen the decision nodeTo freeze a bit node, a nodeIs an information bit node; at the moment, the soft information is updated and calculated in the process of the nodeThe calculation steps related to the above right information are simplified and approximated as nodesThe deletion processing of (1). Approximate deletion nodeThe post-soft information transfer scheme is shown in FIG. 4, which is derived from FIG. 4, and βi tThe related soft information updating calculation process is simplified as follows:
(c) if nodeUpper right informationNode pointUpper right informationThen the decision nodeBeing information bit nodes, nodesIs a frozen bit node; approximating the nodes by the same way as (b)And (5) deleting. Approximate deletion nodeThe post-soft information transfer scheme is shown in FIG. 5, which is obtainable from FIG. 5, andthe related soft information updating calculation process is simplified as follows:
(d) if nodeAnd nodeUpper right informationAre all more than or equal to gamma, then the node is judgedAnd nodeIs a frozen bit node; the soft information updating calculation process comprises the following steps:as can be seen from the simplified soft information update calculation process, approximately deleting a frozen bit node can reduce twiceAnd (6) operation.
The more frozen nodes, the better the computational complexity reduction effect.
In the iterative updating process of the soft information, a path metric value PM is also required to be calculated, the PM is initialized to be 0, when a node corresponding to a frozen bit is encountered, the path metric value is updated, and the updating rule is as follows: PM- λi,i∈F,λiThe left information on the corresponding node is frozen. And when the left information and the right information respectively reach the left side and the right side of the decoding factor graph, the iterative decoding submodule completes decoding to obtain path metric value information.
The decoding bit decision sub-module carries out bit decision operation according to the soft information on the leftmost node of the decoding factor graph,decoding sequence of ith bit nodeλi 0、βi 0Left and right information on the node, respectively.
Step (5) when the parallel decoding of the L simplified soft elimination decoding modules is completed, the decision device module reads the decoding sequence information and the corresponding path metric value information from the L simplified soft elimination decoding modules in sequence and uses the decoding sequence set to collectAnd the path metric set Pi (PM) { PM }0,PM1,…,PML-1Storing in the form of II, selecting the smallest path metric value PM in II (PM) setmin=min{PM0,…,PML-1According to the minimum path metric value PMminAt index positions in the collection, obtaining the collectionCoding sequence of middle corresponding index position
Claims (4)
1. A low complexity reduced soft erasure list decoder for a polar code, comprising:
the device comprises a parameter configuration module, a permutation and arrangement selection module, a preprocessing module, a plurality of simplified soft elimination decoding modules and a decision device module; the simplified soft cancellation decoding module includes: initializing a sub-module, iterating a decoding sub-module and decoding a bit judgment sub-module;
the parameter configuration module is used for providing required information for the subsequent module before decoding begins;
the permutation and arrangement selection module is used for providing a required permutation and arrangement set for a subsequent module;
the preprocessing module is used for carrying out corresponding replacement on the channel receiving information according to the replacement arrangement set;
the simplified soft elimination decoding modules have the same factor graph form, and the simplified soft elimination decoding modules decode in parallel, wherein: the initialization sub-module carries out initial parameter setting on the decoding factor graph; the iterative decoding submodule is used for soft information updating and transmitting operation, decoding nodes are deleted, and nodes in a factor graph are classified by taking initial parameters set on nodes corresponding to freezing positions in the initialization submodule as standards; the decoding bit decision submodule is used for acquiring decoding sequence information;
the decision device module is used for selecting the decoding sequence corresponding to the minimum path metric value and taking out the initial information sequence from the decoding sequence.
2. The method for decoding a reduced soft erasure list using a decoder according to claim 1, wherein the method is embodied as:
step (1) inputs given polarization code parameter information (N, K, F) and received channel log likelihood ratio information LLRs into a parameter configuration module, wherein LLRs is { LLR }0,LLR1,…,LLRN-1Determining index information pos as (0,1, …, N-1) according to the channel log-likelihood ratio information LLRs, wherein N represents a polar code length, K represents an initial information sequence length, F represents a frozen bit index set, and the length is N-K;
carrying out parameter configuration according to the polarization code parameter information, the channel log-likelihood ratio information and the index information, and inputting all information into an information storage unit in a parameter configuration module for a subsequent module to read at any time;
step (2) the permutation and arrangement selection module reads index information from the parameter configuration module and defines the arrangement pi with the length of N00,1, …, N-1 }; will arrange pi0Middle elementPerforming permutation and combination to obtain N! In different arrangements i.e. { π0,π1,…,πN!-1Comparing Hamming distances among the arrays, selecting the first L arrays with large Hamming distances to form an array set pi (pi) ═ pi0,π1,…,πL-1};
And (3) reading the permutation set pi (pi) ═ pi in the permutation and arrangement selection module by the preprocessing module0,π1,…,πL-1And polarization code parameter information (N, K, F) and channel log likelihood ratio information LLRs ═ LLR { (LLR) } in the parameter configuration module0,LLR1,…,LLRN-1And permutation is carried out on the LLRs according to the permutation set pi (pi), and a permutation log likelihood ratio information set pi (LLRs) is obtained0,LLRs1,…,LLRsL-1}=Π[π(LLRs)];
Correspondingly inputting elements in a replacement log-likelihood ratio information set Π (LLRs) into L simplified soft elimination decoding modules with the same factor graph form for parallel decoding, and reading polarization code parameter information (N, K and F) from a preprocessing module by the simplified soft elimination decoding modules; wherein:
(4-1) the initialization submodule carries out initial parameter setting on the decoding factor graph by utilizing the replacement log likelihood ratio information and the polarization code parameter information (N, K, F), and sets left information on the rightmost column node of the decoding factor graphThe initial parameter is the information of the replacement log likelihood ratio, and the right information on the node corresponding to the freezing position of the leftmost column of the factor graph is setThe initial parameter gamma is a positive integer, and the right information initial parameters on the other nodes are set to be 0:i is more than or equal to 0 and less than or equal to N-1, and F is a frozen bit index set;
(4-2) the iterative decoding submodule carries out soft information updating and transmitting operation based on a decoding factor graph structure, and simplification is carried out by deleting decoding nodes in the soft information updating process;
calculating a path metric value PM, initializing the PM to be 0, and updating the path metric value when a node corresponding to a frozen bit is encountered, wherein the updating rule is as follows: PM- λi,i∈F,λiLeft information on the corresponding node of the frozen bit; when the left information and the right information respectively reach the left side and the right side of the decoding factor graph, the iterative decoding submodule completes decoding to obtain path metric value information;
(4-3) the decoding bit decision sub-module carries out bit decision operation according to the soft information on the leftmost node of the decoding factor graph, and the decoding sequence of the ith node Left information and right information on the node respectively;
step (5) when the parallel decoding of the L simplified soft elimination decoding modules is completed, the decision device module reads the decoding sequence information and the corresponding path metric value information from the L simplified soft elimination decoding modules in sequence and uses the decoding sequence set to collectAnd the path metric set Pi (PM) { PM }0,PM1,…,PML-1Storing in the form of II, selecting the smallest path metric value PM in II (PM) setmin=min{PM0,…,PML-1According to the minimum path metric value PMminAt index positions in the collection, obtaining the collectionCoding sequence of middle corresponding index position
4. The reduced soft erasure list decoding method of polar codes according to claim 2, wherein said reduction by decoding node erasure in (4-2) is as follows,for the value of the soft information to be transferred, t is more than or equal to 0 and less than or equal to (log)2N-1):
(a) If nodeAnd nodeUpper right informationAll are less than gamma, then the node is judgedAnd nodeAs information bitsA node; the soft information updating calculation process comprises the following steps:
(b) If nodeUpper right informationNode pointUpper right informationThen the decision nodeTo freeze a bit node, a nodeIs an information bit node; andthe related soft information updating calculation process is simplified as follows:
(c) if nodeUpper right informationNode pointUpper right informationThen the decision nodeBeing information bit nodes, nodesIs a frozen bit node; andthe related soft information updating calculation process is simplified as follows:
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