Title :
Reduced-Complexity Convolutional Self-Doubly Orthogonal Codes for Efficient Iterative Decoding
Author :
Cardinal, Christian ; Haccoun, David ; He, Yu-Cheng
Author_Institution :
Dept. of Electr. Eng., Ecole Polytech. de Montreal, Que.
Abstract :
A variant of convolutional self doubly orthogonal codes that can be decoded using an iterative threshold decoding algorithm is presented. These new codes are called degenerate convolutional self-doubly orthogonal codes since not all the double orthogonality conditions required to obtained convolutional self doubly orthogonal codes defined in the wide sense are satisfied. The memory lengths or spans of the degenerate convolutional self-doubly orthogonal codes are substantially shorter than those of the usual convolutional self doubly orthogonal codes defined in the wide sense, at the cost of only a slight degradation of the error performances. As a consequence, very low complexity implementations are possible with these error correcting schemes. Several new degenerate convolutional self doubly orthogonal codes have been determined and their error performances evaluated using computer simulations
Keywords :
computational complexity; convolutional codes; error correction codes; iterative decoding; error correcting schemes; iterative threshold decoding algorithm; reduced-complexity convolutional codes; self-doubly orthogonal codes; Computer errors; Convolutional codes; Degradation; Encoding; Error correction; Helium; Iterative algorithms; Iterative decoding; Performance evaluation; Shift registers;
Conference_Titel :
Vehicular Technology Conference, 2006. VTC 2006-Spring. IEEE 63rd
Conference_Location :
Melbourne, Vic.
Print_ISBN :
0-7803-9391-0
Electronic_ISBN :
1550-2252
DOI :
10.1109/VETECS.2006.1683059