Decoding method of LDPC codes based on partial average residual belief propagation

1. A decoding method of low-density parity-check (LDPC) codes based on partial average residual belief propagation (PARBP) executed in a computer system, the computer system comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor is operable to execute the computer program so as to implement the decoding method of LDPC codes based on PARBP, wherein the decoding method comprises the following steps:

S1: calculating a cluster size π of a base matrix in a protograph based on a code length m and a code rate of a target codeword;

S2: pre-computing an edge residual r c i →v j corresponding to each edge from a variable node to a check node in a check matrix H, wherein the check matrix H is obtained by lifting the base matrix based on a structural characteristic of the protograph;

S3: calculating, based on π, a partial average residual (PAR) value corresponding to each cluster of m/π clusters in the check matrix H;

S4: sorting the m/π clusters in descending order of corresponding PAR values, and updating an edge with a largest edge residual in each cluster of the m/π clusters;

S5: updating edge information m c i →v j from a check node c i to a variable node v j , and then updating a log-likelihood ratio (LLR) value L(v j ) of the variable node v j ; and

S6: after the updating, making a decoding decision; and if the decoding decision is successful or a maximum number of iterations is reached, ending the decoding; or if the decoding decision is unsuccessful and the maximum number of iterations is not reached, going to step S2 to continue decoding;

wherein a formula for calculating the cluster size π in the protograph in step S1 is as follows:

π= m÷b v

wherein b v is a number of variable nodes in the base matrix and m denotes the code length.

2. The decoding method according to claim 1 , wherein a calculation formula of the edge residual r c i →v j is as a r c i →v j equation listed below:

r c i →v j =∥m c i →v j pre −m c i →v j ∥

wherein m c i →v i represents the edge information from the check node c i to the variable node v j , and is expressed as a m c i →v i equation listed below:

m

c

i

→

v

j

=

2

⁢

tanh

-

1

⁢

{

∏

v

b

∈

N

⁡

(

c

i

)

⁢

\

⁢

v

j

tanh

⁡

(

m

v

b

→

c

i

2

)

}

wherein m v b →c i represents a posterior probability LLR value.

3. The decoding method according to claim 2 , wherein a formula for calculating the PAR value corresponding to each cluster is as follows:

=

Σ

k

=

0

z

0

⁢

❘

"\[LeftBracketingBar]"

r

k

❘

"\[RightBracketingBar]"

z

0

wherein r k represents a residual value of a k-th edge.

4. The decoding method according to claim 3 , wherein an expression for updating the LLR value L(v j ) of the variable node v j is as follows:

L ( v j )=Σ c a ∈M(v j ) m c a →v j +C v j

wherein c v j represents original channel information of the variable node v j , and M(v j ) represents all check nodes connected to the variable node v.

5. The decoding method according to claim 4 , wherein in step S6, specifically, if the decoding decision is unsuccessful and the maximum number of iterations is not reached, edge information from the variable node v j to a check node c a is updated according to the following formula:

m c a →v j =Σ c a′ ∈M(v j )\c a m c a′ →v j C v j

wherein M(v j )\c a represents all the check nodes connected to the variable node v j except the check node c a ; and

edge information is pre-computed for all check nodes c a ∈M(v j )\c i according to the m c i →v i equation, and then an edge residual is calculated according to the r c i →v i equation for a next update iteration process.

6. A non-transitory computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, the steps of the decoding method according to claim 1 are implemented.