A construction technique for random error correcting convolutional codes

Algorithm for constructing random error correcting convolutional code

Convolutional coding techniques for data protection

Results of research on the use of convolutional codes in data communications are presented. Convolutional coding fundamentals are discussed along with modulation and coding interaction. Concatenated coding systems and data compression with convolutional codes are described

Convolutional coding techniques for data protection Quarterly progress report, 16 Nov. 1968 - 15 Feb. 1969

Convolutional coding techniques for data protectio

A Note on the Free Distance of a Convolutional Code

A counterexample to a conjecture on the number of constraint lengths required to achieve the free distance of a rate l/n systematic convolutional code is presented

A Note on the Free Distance of a Convolutional Code

A counterexample to a conjecture on the number of constraint lengths required to achieve the free distance of a rate l/n systematic convolutional code is presented

Further results on binary convolutional codes with an optimum distance profile

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

Subspaces of GF(q)ω and convolutional codes

The present paper is a self-contained treatment of subspaces of the space GF(q)ω of all semi-infinite strings over GF(q). Some necessary and sufficient conditions which characterize those subspaces of GF(q)ω are derived which are convolutional codes, and the classes of subspaces defined by one or more of them are investigated. Moreover structural parameters of convolutional codes such as block length, rate, delay, and constraint length are considered as parameters of subspaces rather than parameters of an encoding device. As a conclusion it is obtained that for error-control purposes none of the investigated superclasses of the class of convolutional codes is better suited than the class of convolutional codes itself

SOME RESULTS ON THE DISTANCE PROPERTIES OF CONVOLUTIONAL CODES

Rate 1/2 binary convolutional codes are analyzed and a lower bound on free distance in terms of the minimum distances of two associated cyclic codes ìs derived. Next, the complexity of computing the free distance is discussed and a counterexample to a conjecture on the relationship of row distance to free distance for systematic codes Ìs presented. Finally, an improved Gilbert bound for definite decoding is derived