Further results on binary convolutional codes with an optimum distance profile (Corresp.)
Rolf Johannesson, Erik Paaske · IEEE Transactions on Information Theory · 1978
Fixed binary convolutional codes are considered which are simultaneously optimal or near-optimal according to three criteria: namely, distance profiled, free distanced_{ \infty}, and minimum number of weightd_{\infty}paths. It is shown how the optimum distance profile criterion can be used to limit the search for codes with a large value ofd_{\infty}. We present extensive lists of such robustly optimal codes containing rateR = l/2nonsystematic codes, several withd_{\infty}superior to that of any previously known code of the same rate and memory; rateR = 2/3systematic codes; and rateR = 2/3nonsystematic codes. As a counterpart to quick-look-in (QLI) codes which are not "transparent," we introduce rateR = 1/2easy-look-in-transparent (ELIT) codes with a feedforward inverse(1 + D,D). In general, ELIT codes haved_{\infty}superior to that of QLI codes.