Title :
A class of turbo-like LDPC codes and their decoding based on neural network
Author :
Zhao, Zijian ; Wu, Xiaojuan ; Yang, Jun
Author_Institution :
Sch. of Inf. Sci. & Eng., Shandong Univ., Jinan, China
Abstract :
Turbo codes and LDPC codes are both superior to other error correcting codes. These two families of codes have some similarities. It seems a good idea to design new codes combining these two codes. Through the analysis of turbo codes, we can consider turbo codes as block codes and find their matrix H. In this paper, we give a new class of turbo-like LDPC codes combining the advantages of turbo and LDPC codes and a decoding method based on neural network. A lot of simulations have been made and the results reveal that these codes have robuster performance than turbo codes.
Keywords :
block codes; decoding; error correction codes; matrix algebra; neural nets; parity check codes; telecommunication computing; turbo codes; block code; decoding method; error correcting code; low-density parity check; neural network; turbo-like LDPC codes; AWGN; Bit error rate; Decoding; Error correction codes; Fading; Message passing; Neural networks; Parity check codes; Sparse matrices; Turbo codes; Hopfield Network; LDPC Codes; Message Passing; Self-loop; Sparse Matrix; Sum-product Algorithm; Turbo Codes; Turbo-like Codes;
Conference_Titel :
Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications, 2005. MAPE 2005. IEEE International Symposium on
Print_ISBN :
0-7803-9128-4
DOI :
10.1109/MAPE.2005.1618080
