2 results about "Tanner graph" patented technology

Various aspects of the present disclosure relate to enhanced encoder designs (and associated signaling), such as enhanced encoder structures for quasi-cyclic low-density parity-check (QC-LDPC) encoders. The new encoders can achieve a larger girth (e.g., length of the shortest cycle of a Tanner graph) by using permutation matrices without increasing the complexity of hardware implementations of the encoders. Thus, the enhanced encoders can facilitate use of short or limited length codes for wireless communication data channels, among other benefits.

This invention relates to a Normalized Minimum Offset Sum (NOMS) decoding method for LDPC codes based on optimized grouped neural networks, belonging to the field of wireless communication channel coding technology. This method utilizes the topological relationship between the LDPC code base graph and the Tanner graph to transform the Tanner graph into a non-fully connected grouped neural network. It groups edges based on the base graph type and achieves parameter sharing using edge bundles. A greedy hierarchical training algorithm is used to optimize the normalization factor and offset factor round by round, obtaining dynamically adaptive parameters that adapt to each iteration stage. The optimized factors are substituted into the decoding update formula to replace the traditional fixed factors and complete the normalized minimum offset sum decoding. This invention can suppress error amplification during iteration, avoid error leveling and decoding deadlock, improve decoding accuracy while reducing computational complexity and parameter size, exhibit strong generalization ability, and can adapt to LDPC codes with different code lengths and rates under the same base graph. It also features low latency, high robustness, and engineering practicality.