Title :
New syndrome decoding techniques for the (n,k) convolutional codes
Author :
Reed, I.S. ; Truong, T.K.
Author_Institution :
University of Southern California, Department of Electrical Engineering, Los Angeles, USA
fDate :
7/1/1984 12:00:00 AM
Abstract :
This paper presents a new syndrome decoding algorithm for the (n,k) convolutional codes (CCs). The construction of the trellis diagram of this algorithm is simpler than the syndrome decoding algorithms of Schalkwijk, Vinck and De Paepe. The new algorithm is based on the general solution of the syndrome equation, a linear diophantine equation for the error polynomial vector E(D). The set of diophantine solutions is a coset of the CC. In this error coset a recursive, Viterbi-like, algorithm is developed to find the minimum weight error vector ¿¿(D). An example, illustrating the new decoding algorithm is given for the binary nonsystematic (3,1) CC.
Keywords :
codes; decoding; (n,k) convolution codes; algorithm; binary nonsystematic (3,1) convolutional code; error polynomial vector; linear diophantine equation; minimum weight error vector; recursive Viterbi-like algorithm; syndrome decoding techniques; trellis diagram;
Journal_Title :
Communications, Radar and Signal Processing, IEE Proceedings F
DOI :
10.1049/ip-f-1.1984.0063