Polar Channel Encoding Using Row-Layer Bit Placement
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Solution Overview
Problem
Polar codes exhibit a high false alarm rate (FAR) in decoding processes, which affects the reliability of data transmission in communications systems.
Innovation Solution
A channel encoding method that generates a new matrix G'N by considering both row and layer locations of information bits in the encoding diagram, using a Kronecker product of matrices F2, to improve the distribution of information bits and reduce bit error rates, and determines whether to stop the decoding algorithm based on cyclic redundancy check (CRC).
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional polar code encoding is used, then encoding complexity is low and Shannon capacity is achieved, but false alarm rate in decoding is high
Solution Approach 1:
The encoding process is segmented into multiple stages: generating the polar code generator matrix, determining information bit locations in the encoding diagram, and constructing the new generator matrix G'N by selecting specific rows and layers. This segmentation allows the system to maintain low complexity while improving reliability through structured modifications to the encoding process.
Solution Approach 2:
The patent introduces a new dimension to the traditional polar code by considering both row locations and layer locations in the encoding diagram. This two-dimensional location specification (row index set H and layer index set M) transforms the conventional one-dimensional approach, enabling better error correction performance without significantly increasing complexity.
2Reliability
If information bits are distributed only by row location, then encoding is simple, but bit error rate is high
Solution Approach 1:
The patent applies local quality by differentiating the treatment of different positions in the encoding diagram. Information bits are assigned to specific row locations H and layer locations M, creating a non-uniform distribution pattern. This localized optimization of bit placement improves error correction performance by strategically positioning information bits in more reliable positions while keeping frozen bits in less reliable positions.
Solution Approach 2:
The system performs preliminary action by pre-determining the optimal locations of information bits in the encoding diagram before the actual encoding process. The row location index set H and layer location index set M are calculated in advance based on the desired code rate and block length, allowing the encoder to efficiently construct the new generator matrix G'N without complex real-time decisions during encoding.
Data Source
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AI summary
This application provides a channel encoding method, an encoding apparatus, and a system. A bit sequence X1N is output by using X1N = D1NFN, where D1N is a bit sequence obtained after an input bit sequence u1N is encoded based on locations of K to-be-encoded information bits in an encoding diagram that has a mother code length of N, u1N is a bit sequence obtained based on the K to-be-encoded information bits, and FN is a Kronecker product of log2 N matrices F2. In the foregoing technical solution, in particular, a design considers that the locations of the K to-be-encoded information bits in the encoding diagram that has a mother code length of N include a row location index set H of the information bits in the encoding diagram and a layer location index set M of the information bits in the encoding diagram, where 0 ≤ H ≤ N, and 0 < M ≤ logm N -1. The locations of the information bits in the design are applied to an encoding process, so that a bit error rate is reduced, bit error rate performance of a system is greatly improved, and false alarm rate performance of decoding is further improved.