Journal of Xidian University ›› 2024, Vol. 51 ›› Issue (6): 52-59.doi: 10.19665/j.issn1001-2400.20240912

• Information and Communications Engineering • Previous Articles     Next Articles

Optimization method for Raptor-like multi-rate QC-LDPC codes

LI Hua’an1,2(), WANG Wenzhen2(), XU Hengzhou3(), CHEN Chao2(), BAI Baoming2()   

  1. 1. College of Physics and Telecommunication Engineering,Zhoukou Normal University,Zhoukou 466001,China
    2. State Key Laboratory of Integrated Service Networks,Xidian University,Xi’an 710071,China
    3. School of Computer,Henan University of Engineering,Zhengzhou 450000,China
  • Received:2024-02-20 Online:2024-12-20 Published:2024-10-08

Abstract:

Design optimization of high-performance low-density parity-check(LDPC) codes for the future communication network can reduce to the design category of LDPC codes with a lower description complexity,such as multi-rate LDPC(MR-LDPC) codes with constant codeword length.By combining the structural property of both 5G LDPC codes and MR codes,Raptor-like multi-rate quasi-cyclic LDPC(RL-MR-QC-LDPC) codes provide a promising scheme for the coding method fusion design of the future ground network and other communication systems.Since the construction involves algebraic theory,the design/storage complexity of algebraic RL-MR-QC-LDPC codes is very low,but since the algebraically constructed matrix is too structured,the performance improvement is not obvious.Therefore,this paper presents an optimization method for the RL-MR-QC-LDPC codes by using what is called the splitting-combining strategy.Numerical results show that in comparison to the original codes,the optimized codes can obtain a better overall performance.The proposed method can be used directly to optimize the RL-MR-QC-LDPC codes and can also be a post-processing method to improve the algebraic RL-MR-QC-LDPC codes so that it can help derive the coding method fusion design of the future ground network and other communication systems.

Key words: low-density parity-check codes, Raptor-like, multi-rate, quasi-cyclic, optimization

CLC Number: 

  • TN911.22