BP equalization method, device, communication apparatus and storage medium

A Belief Propagation (BP) equalization apparatus applied to a communication device, comprising:

• a splitting module configured to split a received signal Yc, a channel estimation Hc and a symbol estimation Xc into real parts and imaginary parts to obtain a received signal matrix Y, a channel estimation matrix H and a symbol estimation matrix X;
• a decomposition module configured to perform QR decomposition on the channel estimation matrix H to obtain an equivalent received signal Ybp, an equivalent channel R and a noise power σ2;
• and
• an iteration module configured to perform iteration based on the equivalent received signal Ybp, the equivalent channel R and the noise power σ2 obtain a position probability of per stream symbol;
• wherein the iteration module is configured to:
• construct a fully connected BP network by taking the equivalent received signal Ybp as an observation node and the symbol estimation matrix X as an information node, and
• initialize a per stream symbol position probability as
• Pro
• =
• 1
• M
• ·
• I
• M
• ×
• 2
• ·
• flow
• ,
• M being an order of quadrature amplitude modulation (QAM), IM×2,flow being an identity matrix;
• calculate an equivalent received signal mean Su,ONI and an equivalent received signal variance estimate Sσ2,ONI on each observation node index ONI={2·flow, . . . , 1} and
• calculate a per stream symbol likelihood probability llr∈RM×1 and a per stream belief probability proT∈RM×1 according to the equivalent received signal mean Su,ONI and the equivalent received signal variance estimate Sσ2,ONI.

A communication device, comprising:

• a memory storing a computer program;
• a processor configured to execute the computer program to carry out a Belief Propagation (BP) equalization method applied to the communication device comprising:
• splitting a received signal Yc, a channel estimation Hc and a symbol estimation Xc into real parts and imaginary parts to obtain a received signal matrix Y, a channel estimation matrix H and a symbol estimation matrix X;
• performing orthogonal triangular (QR) decomposition on the channel estimation matrix H to obtain an equivalent received signal Ybp, an equivalent channel R and a noise power σ2;
• and
• performing iteration based on the equivalent received signal Ybp, the equivalent channel R and the noise power σ2 to obtain a position probability of per stream symbol;
• wherein performing iteration based on the equivalent received signal Ybp, the equivalent channel R and the noise power σ2 to obtain a position probability of per stream symbol comprises:
• constructing a fully connected BP network by taking the equivalent received signal Ybp as an observation node and the symbol estimation matrix X as an information node, and
• initializing a per stream symbol position probability as
• Pro
• =
• 1
• M
• ·
• I
• M
• ×
• 2
• ·
• flow
• ,
• M being an order of quadrature amplitude modulation (QAM), IM×2,flow being an identity matrix;
• calculating an equivalent received signal mean Su,ONI and an equivalent received signal variance estimate Sσ2,ONI on each observation node index ONI={2·flow, . . . , 1};
• and
• calculating a per stream symbol likelihood probability llr∈RM×1 and a per stream belief probability proT∈RM×1 according to the equivalent received signal mean Su,ONI and the equivalent received signal variance estimate Sσ2,ONI;
• and
• a communication bus configured to connect the processor to the memory.