Title :
A CAM-based decoder of convolutionally-encoded data
Author :
Wu, Yu-Jhih ; Alston, Michael D. ; Chau, Paul M.
Author_Institution :
Dept. of Electr. & Comput. Eng., California Univ., San Diego, La Jolla, CA, USA
Abstract :
Presented is a new VLSI architecture for decoding convolutionally encoded digital data for short (K⩽=9) as well as long (K>9) constraint-length (K) codes. Shift-invariant relationships between clusters of channel symbols derived from the particular code in use are used to generate error pattern sequence syndromes which address a bank consisting of content addressable memory (CAM) containing channel error scenarios. This approach combined with decision feedback techniques allows the correction of certain classes of channel symbol errors without hypothesizing the state of the encoder
Keywords :
VLSI; computer architecture; content-addressable storage; decoding; error correction; special purpose computers; CAM-based decoder; VLSI architecture; channel error scenarios; content addressable memory; decision feedback techniques; decoding convolutionally encoded digital data; error correction; error pattern sequence syndromes; CADCAM; Computer aided manufacturing; Converters; Convolutional codes; Decoding; Equations; Error correction; Shift registers; Very large scale integration; Viterbi algorithm;
Conference_Titel :
Circuits and Systems, 1991., IEEE International Sympoisum on
Print_ISBN :
0-7803-0050-5
DOI :
10.1109/ISCAS.1991.176165
