A New Approach for the Construction of Powerful LDPC Convolutional Codes
A novel approach for the algebraic construction of Low-Density Parity-Check (LDPC) convolutional codes is presented. It is based on the orthogonality structures of the codes. The proposed code construction leads to a girth of at least 10 in the Tanner graph. The error performance of these codes compares favorably with the usual LDPC convolutional codes, especially at low signal-to-noise ratio range. Algebraic constructions for Low-Density Parity-Check (LDPC) codes yield low encoding complexity as well as efficient implementation of iterative Belief Propagation (BP) decoding. A large number of algebraic constructions, including quasi-cyclic and finite geometry constructions, have been presented.