On the error exponent for woven convolutional codes with inner warp
Victor Zyablov, Sergo Shavgulidze, Rolf Johannesson · IEEE Transactions on Information Theory · 2001
In this correspondence, the error exponents and decoding complexity of binary woven convolutional codes with outer and inner warp are studied. It is shown that for both constructions an error probability that is exponentially decreasing with the memory of the woven convolutional codes can be achieved with a nonexponentially increasing decoding complexity. Furthermore, the error exponent for woven convolutional codes with inner warp is larger than the one for woven convolutional codes with outer warp.