Codeword Structure Analysis for LDPC Convolutional Codes
Hua Zhou,
Jiao Feng,
Peng Li,
Jingming Xia
Affiliations
Hua Zhou
Jiangsu Key Laboratory of Meteorological Observation and Information Processing, Nanjing University of Information Science and Technology, Ningliu Road No. 219, Nanjing 210044, China
Jiao Feng
Jiangsu Key Laboratory of Meteorological Observation and Information Processing, Nanjing University of Information Science and Technology, Ningliu Road No. 219, Nanjing 210044, China
Peng Li
Jiangsu Key Laboratory of Meteorological Observation and Information Processing, Nanjing University of Information Science and Technology, Ningliu Road No. 219, Nanjing 210044, China
Jingming Xia
Jiangsu Key Laboratory of Meteorological Observation and Information Processing, Nanjing University of Information Science and Technology, Ningliu Road No. 219, Nanjing 210044, China
The codewords of a low-density parity-check (LDPC) convolutional code (LDPC-CC) are characterised into structured and non-structured. The number of the structured codewords is dominated by the size of the polynomial syndrome former matrix H T ( D ) , while the number of the non-structured ones depends on the particular monomials or polynomials in H T ( D ) . By evaluating the relationship of the codewords between the mother code and its super codes, the low weight non-structured codewords in the super codes can be eliminated by appropriately choosing the monomials or polynomials in H T ( D ) , resulting in improved distance spectrum of the mother code.
